Overview

Dataset statistics

Number of variables79
Number of observations11114
Missing cells460154
Missing cells (%)52.4%
Total size in memory6.7 MiB
Average record size in memory632.0 B

Variable types

Text9
Numeric70

Alerts

city has constant value "Johannesburg"Constant
hiv_status has constant value "Positive"Constant
on_art has constant value "1.0"Constant
calcium has constant value "2.31"Constant
patient_id has 263 (2.4%) missing valuesMissing
visit_date has 263 (2.4%) missing valuesMissing
year has 263 (2.4%) missing valuesMissing
month has 263 (2.4%) missing valuesMissing
season has 263 (2.4%) missing valuesMissing
city has 263 (2.4%) missing valuesMissing
age_years has 1628 (14.6%) missing valuesMissing
sex has 1333 (12.0%) missing valuesMissing
race has 7148 (64.3%) missing valuesMissing
hiv_status has 4888 (44.0%) missing valuesMissing
hiv_positive has 427 (3.8%) missing valuesMissing
on_art has 10637 (95.7%) missing valuesMissing
virally_suppressed has 8593 (77.3%) missing valuesMissing
cd4_count has 6559 (59.0%) missing valuesMissing
viral_load has 8594 (77.3%) missing valuesMissing
viral_load_undetectable has 8594 (77.3%) missing valuesMissing
log10_viral_load has 8597 (77.4%) missing valuesMissing
viral_load_wrhi003_category has 10893 (98.0%) missing valuesMissing
hemoglobin has 8078 (72.7%) missing valuesMissing
hematocrit has 8397 (75.6%) missing valuesMissing
rbc_count has 10062 (90.5%) missing valuesMissing
wbc_count has 8087 (72.8%) missing valuesMissing
platelet_count has 8792 (79.1%) missing valuesMissing
mcv has 10062 (90.5%) missing valuesMissing
mch has 10062 (90.5%) missing valuesMissing
mchc has 10062 (90.5%) missing valuesMissing
rdw has 10897 (98.0%) missing valuesMissing
neutrophils_pct has 9831 (88.5%) missing valuesMissing
lymphocytes_pct has 9831 (88.5%) missing valuesMissing
monocytes_pct has 10897 (98.0%) missing valuesMissing
eosinophils_pct has 10897 (98.0%) missing valuesMissing
basophils_pct has 10897 (98.0%) missing valuesMissing
fasting_glucose has 8346 (75.1%) missing valuesMissing
log10_fasting_glucose has 8346 (75.1%) missing valuesMissing
total_cholesterol has 8145 (73.3%) missing valuesMissing
hdl_cholesterol has 8152 (73.3%) missing valuesMissing
ldl_cholesterol has 8174 (73.5%) missing valuesMissing
triglycerides has 10142 (91.3%) missing valuesMissing
creatinine has 9862 (88.7%) missing valuesMissing
creatinine_clearance has 10893 (98.0%) missing valuesMissing
bun has 11024 (99.2%) missing valuesMissing
alt has 9422 (84.8%) missing valuesMissing
ast has 9437 (84.9%) missing valuesMissing
alp has 10083 (90.7%) missing valuesMissing
total_bilirubin has 10083 (90.7%) missing valuesMissing
albumin has 9142 (82.3%) missing valuesMissing
total_protein has 10185 (91.6%) missing valuesMissing
sodium has 10083 (90.7%) missing valuesMissing
potassium has 9904 (89.1%) missing valuesMissing
calcium has 11113 (> 99.9%) missing valuesMissing
systolic_bp has 5938 (53.4%) missing valuesMissing
diastolic_bp has 5938 (53.4%) missing valuesMissing
heart_rate has 6596 (59.3%) missing valuesMissing
temperature has 6826 (61.4%) missing valuesMissing
respiratory_rate has 8941 (80.4%) missing valuesMissing
oxygen_saturation has 8987 (80.9%) missing valuesMissing
height_m has 4609 (41.5%) missing valuesMissing
weight_kg has 4477 (40.3%) missing valuesMissing
bmi has 4503 (40.5%) missing valuesMissing
waist_circumference has 10537 (94.8%) missing valuesMissing
temp_mean_c has 263 (2.4%) missing valuesMissing
temp_max_c has 263 (2.4%) missing valuesMissing
temp_min_c has 263 (2.4%) missing valuesMissing
temp_range_c has 263 (2.4%) missing valuesMissing
temp_lag1d has 263 (2.4%) missing valuesMissing
temp_lag3d has 263 (2.4%) missing valuesMissing
temp_lag7d has 263 (2.4%) missing valuesMissing
temp_lag14d has 263 (2.4%) missing valuesMissing
temp_lag21d has 263 (2.4%) missing valuesMissing
temp_lag30d has 263 (2.4%) missing valuesMissing
temp_variability_7d has 263 (2.4%) missing valuesMissing
temp_variability_30d has 263 (2.4%) missing valuesMissing
apparent_temp has 263 (2.4%) missing valuesMissing
temp_anomaly has 263 (2.4%) missing valuesMissing
heat_stress_category has 263 (2.4%) missing valuesMissing
hiv_positive has 4461 (40.1%) zerosZeros
virally_suppressed has 2265 (20.4%) zerosZeros
viral_load_undetectable has 2271 (20.4%) zerosZeros
log10_viral_load has 244 (2.2%) zerosZeros
viral_load_wrhi003_category has 179 (1.6%) zerosZeros
heat_wave_day has 10387 (93.5%) zerosZeros

Reproduction

Analysis started2025-11-25 14:51:33.023537
Analysis finished2025-11-25 14:51:33.337910
Duration0.31 seconds
Software versionydata-profiling vv4.18.0
Download configurationconfig.json

Variables

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:33.360581image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.45348209
Min length12

Characters and Unicode

Total characters138408
Distinct characters35
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJHB_WRHI_003
2nd rowJHB_WRHI_003
3rd rowJHB_WRHI_003
4th rowJHB_WRHI_003
5th rowJHB_WRHI_003
ValueCountFrequency (%)
jhb_aurum_0092930
26.4%
jhb_vida_0072129
19.2%
jhb_wrhi_0011067
 
9.6%
jhb_ezin_0021053
 
9.5%
jhb_dphru_053998
 
9.0%
jhb_dphru_013784
 
7.1%
jhb_vida_008550
 
4.9%
jhb_actg_019283
 
2.5%
jhb_actg_015264
 
2.4%
jhb_actg_018240
 
2.2%
Other values (7)816
 
7.3%
2025-11-25T16:51:33.480195image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_22228
16.1%
019228
13.9%
H14348
10.4%
J11114
 
8.0%
B11114
 
8.0%
A6812
 
4.9%
u5860
 
4.2%
D4461
 
3.2%
I4146
 
3.0%
R3234
 
2.3%
Other values (25)35863
25.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter67959
49.1%
Decimal Number33342
24.1%
Connector Punctuation22228
 
16.1%
Lowercase Letter14879
 
10.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
H14348
21.1%
J11114
16.4%
B11114
16.4%
A6812
10.0%
D4461
 
6.6%
I4146
 
6.1%
R3234
 
4.8%
V2679
 
3.9%
P1946
 
2.9%
U1782
 
2.6%
Other values (8)6323
9.3%
Decimal Number
ValueCountFrequency (%)
019228
57.7%
93213
 
9.6%
12890
 
8.7%
72149
 
6.4%
32003
 
6.0%
51441
 
4.3%
21310
 
3.9%
8790
 
2.4%
6316
 
0.9%
42
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
u5860
39.4%
m2930
19.7%
r2930
19.7%
n1053
 
7.1%
i1053
 
7.1%
z1053
 
7.1%
Connector Punctuation
ValueCountFrequency (%)
_22228
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin82838
59.9%
Common55570
40.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
H14348
17.3%
J11114
13.4%
B11114
13.4%
A6812
8.2%
u5860
 
7.1%
D4461
 
5.4%
I4146
 
5.0%
R3234
 
3.9%
m2930
 
3.5%
r2930
 
3.5%
Other values (14)15889
19.2%
Common
ValueCountFrequency (%)
_22228
40.0%
019228
34.6%
93213
 
5.8%
12890
 
5.2%
72149
 
3.9%
32003
 
3.6%
51441
 
2.6%
21310
 
2.4%
8790
 
1.4%
6316
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII138408
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_22228
16.1%
019228
13.9%
H14348
10.4%
J11114
 
8.0%
B11114
 
8.0%
A6812
 
4.9%
u5860
 
4.2%
D4461
 
3.2%
I4146
 
3.0%
R3234
 
2.3%
Other values (25)35863
25.9%

patient_id
Text

Missing 

Distinct9756
Distinct (%)89.9%
Missing263
Missing (%)2.4%
Memory size87.0 KiB
2025-11-25T16:51:33.578703image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length33
Median length17
Mean length20.65496268
Min length14

Characters and Unicode

Total characters224127
Distinct characters25
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9356 ?
Unique (%)86.2%

Sample

1st rowHEAT_329E55DDD278
2nd rowHEAT_C8A77DD97D98
3rd rowHEAT_A4407F8E079E
4th rowHEAT_7DCC7C7F1641
5th rowHEAT_32253618AEF8
ValueCountFrequency (%)
heat_aurum_nan380
 
3.5%
heat_80b29fc116a34
 
< 0.1%
heat_e645985e368f4
 
< 0.1%
heat_1ca0fecca09c4
 
< 0.1%
heat_c15b9290e25d4
 
< 0.1%
heat_9d48a6fffc6e4
 
< 0.1%
heat_d2bc408693dd4
 
< 0.1%
heat_fa125e7357824
 
< 0.1%
heat_2daa2908c08e4
 
< 0.1%
heat_4df14a36d7ce4
 
< 0.1%
Other values (9746)10435
96.2%
2025-11-25T16:51:33.700959image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A22186
 
9.9%
E16901
 
7.5%
015165
 
6.8%
_13781
 
6.1%
112895
 
5.8%
-12750
 
5.7%
911828
 
5.3%
H10851
 
4.8%
T10851
 
4.8%
59687
 
4.3%
Other values (15)87232
38.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter101224
45.2%
Decimal Number95232
42.5%
Connector Punctuation13781
 
6.1%
Dash Punctuation12750
 
5.7%
Lowercase Letter1140
 
0.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A22186
21.9%
E16901
16.7%
H10851
10.7%
T10851
10.7%
U8410
 
8.3%
D6021
 
5.9%
C5930
 
5.9%
B5837
 
5.8%
F5827
 
5.8%
R5480
 
5.4%
Decimal Number
ValueCountFrequency (%)
015165
15.9%
112895
13.5%
911828
12.4%
59687
10.2%
79283
9.7%
27861
8.3%
37592
8.0%
47326
7.7%
66914
7.3%
86681
7.0%
Lowercase Letter
ValueCountFrequency (%)
n760
66.7%
a380
33.3%
Connector Punctuation
ValueCountFrequency (%)
_13781
100.0%
Dash Punctuation
ValueCountFrequency (%)
-12750
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common121763
54.3%
Latin102364
45.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
A22186
21.7%
E16901
16.5%
H10851
10.6%
T10851
10.6%
U8410
 
8.2%
D6021
 
5.9%
C5930
 
5.8%
B5837
 
5.7%
F5827
 
5.7%
R5480
 
5.4%
Other values (3)4070
 
4.0%
Common
ValueCountFrequency (%)
015165
12.5%
_13781
11.3%
112895
10.6%
-12750
10.5%
911828
9.7%
59687
8.0%
79283
7.6%
27861
6.5%
37592
6.2%
47326
6.0%
Other values (2)13595
11.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII224127
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A22186
 
9.9%
E16901
 
7.5%
015165
 
6.8%
_13781
 
6.1%
112895
 
5.8%
-12750
 
5.7%
911828
 
5.3%
H10851
 
4.8%
T10851
 
4.8%
59687
 
4.3%
Other values (15)87232
38.9%

visit_date
Text

Missing 

Distinct1731
Distinct (%)16.0%
Missing263
Missing (%)2.4%
Memory size87.0 KiB
2025-11-25T16:51:33.780029image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters108510
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique292 ?
Unique (%)2.7%

Sample

1st row2016-07-19
2nd row2016-07-19
3rd row2016-07-19
4th row2016-07-19
5th row2016-07-19
ValueCountFrequency (%)
2017-01-01162
 
1.5%
2020-08-1882
 
0.8%
2020-08-1775
 
0.7%
2020-08-0771
 
0.7%
2020-08-1168
 
0.6%
2020-08-1263
 
0.6%
2020-07-2362
 
0.6%
2020-07-3056
 
0.5%
2020-08-0454
 
0.5%
2020-08-0350
 
0.5%
Other values (1721)10108
93.2%
2025-11-25T16:51:33.902744image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
028068
25.9%
-21702
20.0%
219836
18.3%
116814
15.5%
74453
 
4.1%
34421
 
4.1%
43655
 
3.4%
83452
 
3.2%
62271
 
2.1%
51999
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number86808
80.0%
Dash Punctuation21702
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
028068
32.3%
219836
22.9%
116814
19.4%
74453
 
5.1%
34421
 
5.1%
43655
 
4.2%
83452
 
4.0%
62271
 
2.6%
51999
 
2.3%
91839
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
-21702
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common108510
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
028068
25.9%
-21702
20.0%
219836
18.3%
116814
15.5%
74453
 
4.1%
34421
 
4.1%
43655
 
3.4%
83452
 
3.2%
62271
 
2.1%
51999
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII108510
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
028068
25.9%
-21702
20.0%
219836
18.3%
116814
15.5%
74453
 
4.1%
34421
 
4.1%
43655
 
3.4%
83452
 
3.2%
62271
 
2.1%
51999
 
1.8%

year
Real number (ℝ)

Missing 

Distinct17
Distinct (%)0.2%
Missing263
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean2015.502442
Minimum2003
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:33.950428image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum2003
5-th percentile2011
Q12013
median2014
Q32020
95-th percentile2020
Maximum2021
Range18
Interquartile range (IQR)7

Descriptive statistics

Standard deviation3.70600068
Coefficient of variation (CV)0.001838747799
Kurtosis-0.2231586951
Mean2015.502442
Median Absolute Deviation (MAD)3
Skewness-0.4223368305
Sum21870217
Variance13.73444104
MonotonicityNot monotonic
2025-11-25T16:51:33.991955image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
20202557
23.0%
20132061
18.5%
20141831
16.5%
20171667
15.0%
2018648
 
5.8%
2011615
 
5.5%
2012513
 
4.6%
2006313
 
2.8%
2021301
 
2.7%
2016120
 
1.1%
Other values (7)225
 
2.0%
(Missing)263
 
2.4%
ValueCountFrequency (%)
20035
 
< 0.1%
200415
 
0.1%
200519
 
0.2%
2006313
2.8%
200798
 
0.9%
ValueCountFrequency (%)
2021301
 
2.7%
20202557
23.0%
2018648
 
5.8%
20171667
15.0%
2016120
 
1.1%

month
Real number (ℝ)

Missing 

Distinct12
Distinct (%)0.1%
Missing263
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean6.543452216
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:34.030593image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q39
95-th percentile11
Maximum12
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.958674854
Coefficient of variation (CV)0.4521580897
Kurtosis-0.8768815603
Mean6.543452216
Median Absolute Deviation (MAD)2
Skewness-0.2331275948
Sum71003
Variance8.753756892
MonotonicityNot monotonic
2025-11-25T16:51:34.067399image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
81702
15.3%
71573
14.2%
101134
10.2%
5942
8.5%
6899
8.1%
9817
7.4%
2814
7.3%
4750
6.7%
3684
6.2%
11658
 
5.9%
Other values (2)878
7.9%
ValueCountFrequency (%)
1625
5.6%
2814
7.3%
3684
6.2%
4750
6.7%
5942
8.5%
ValueCountFrequency (%)
12253
 
2.3%
11658
 
5.9%
101134
10.2%
9817
7.4%
81702
15.3%

season
Text

Missing 

Distinct4
Distinct (%)< 0.1%
Missing263
Missing (%)2.4%
Memory size87.0 KiB
2025-11-25T16:51:34.100018image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters65106
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowWinter
2nd rowWinter
3rd rowWinter
4th rowWinter
5th rowWinter
ValueCountFrequency (%)
winter4174
38.5%
spring2609
24.0%
autumn2376
21.9%
summer1692
15.6%
2025-11-25T16:51:34.175302image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n9159
14.1%
r8475
13.0%
i6783
10.4%
t6550
10.1%
u6444
9.9%
e5866
9.0%
m5760
8.8%
S4301
6.6%
W4174
6.4%
p2609
 
4.0%
Other values (2)4985
7.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter54255
83.3%
Uppercase Letter10851
 
16.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n9159
16.9%
r8475
15.6%
i6783
12.5%
t6550
12.1%
u6444
11.9%
e5866
10.8%
m5760
10.6%
p2609
 
4.8%
g2609
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
S4301
39.6%
W4174
38.5%
A2376
21.9%

Most occurring scripts

ValueCountFrequency (%)
Latin65106
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n9159
14.1%
r8475
13.0%
i6783
10.4%
t6550
10.1%
u6444
9.9%
e5866
9.0%
m5760
8.8%
S4301
6.6%
W4174
6.4%
p2609
 
4.0%
Other values (2)4985
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII65106
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n9159
14.1%
r8475
13.0%
i6783
10.4%
t6550
10.1%
u6444
9.9%
e5866
9.0%
m5760
8.8%
S4301
6.6%
W4174
6.4%
p2609
 
4.0%
Other values (2)4985
7.7%

latitude
Real number (ℝ)

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-26.08390367
Minimum-26.2309
Maximum-25.7479
Zeros0
Zeros (%)0.0%
Negative11114
Negative (%)100.0%
Memory size87.0 KiB
2025-11-25T16:51:34.211006image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-26.2309
5-th percentile-26.2041
Q1-26.2041
median-26.2041
Q3-25.7479
95-th percentile-25.7479
Maximum-25.7479
Range0.483
Interquartile range (IQR)0.4562

Descriptive statistics

Standard deviation0.2010596575
Coefficient of variation (CV)-0.007708188929
Kurtosis-0.8487392469
Mean-26.08390367
Median Absolute Deviation (MAD)0
Skewness1.072910888
Sum-289896.5054
Variance0.04042498587
MonotonicityNot monotonic
2025-11-25T16:51:34.243690image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
-26.20418154
73.4%
-25.74792930
 
26.4%
-26.230930
 
0.3%
ValueCountFrequency (%)
-26.230930
 
0.3%
-26.20418154
73.4%
-25.74792930
 
26.4%
ValueCountFrequency (%)
-25.74792930
 
26.4%
-26.20418154
73.4%
-26.230930
 
0.3%

longitude
Real number (ℝ)

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.08559679
Minimum27.8585
Maximum28.2293
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:34.274298image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum27.8585
5-th percentile27.9394
Q128.0473
median28.0473
Q328.2293
95-th percentile28.2293
Maximum28.2293
Range0.3708
Interquartile range (IQR)0.182

Descriptive statistics

Standard deviation0.09139356213
Coefficient of variation (CV)0.003254107891
Kurtosis-0.7083367318
Mean28.08559679
Median Absolute Deviation (MAD)0
Skewness0.5878069058
Sum312143.3227
Variance0.008352783199
MonotonicityNot monotonic
2025-11-25T16:51:34.313235image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
28.04737209
64.9%
28.22932930
26.4%
27.9394945
 
8.5%
27.858530
 
0.3%
ValueCountFrequency (%)
27.858530
 
0.3%
27.9394945
 
8.5%
28.04737209
64.9%
28.22932930
26.4%
ValueCountFrequency (%)
28.22932930
26.4%
28.04737209
64.9%
27.9394945
 
8.5%
27.858530
 
0.3%

city
Text

Constant  Missing 

Distinct1
Distinct (%)< 0.1%
Missing263
Missing (%)2.4%
Memory size87.0 KiB
2025-11-25T16:51:34.351357image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters130212
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJohannesburg
2nd rowJohannesburg
3rd rowJohannesburg
4th rowJohannesburg
5th rowJohannesburg
ValueCountFrequency (%)
johannesburg10851
100.0%
2025-11-25T16:51:34.423784image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n21702
16.7%
J10851
8.3%
o10851
8.3%
h10851
8.3%
a10851
8.3%
e10851
8.3%
s10851
8.3%
b10851
8.3%
u10851
8.3%
r10851
8.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter119361
91.7%
Uppercase Letter10851
 
8.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n21702
18.2%
o10851
9.1%
h10851
9.1%
a10851
9.1%
e10851
9.1%
s10851
9.1%
b10851
9.1%
u10851
9.1%
r10851
9.1%
g10851
9.1%
Uppercase Letter
ValueCountFrequency (%)
J10851
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin130212
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n21702
16.7%
J10851
8.3%
o10851
8.3%
h10851
8.3%
a10851
8.3%
e10851
8.3%
s10851
8.3%
b10851
8.3%
u10851
8.3%
r10851
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII130212
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n21702
16.7%
J10851
8.3%
o10851
8.3%
h10851
8.3%
a10851
8.3%
e10851
8.3%
s10851
8.3%
b10851
8.3%
u10851
8.3%
r10851
8.3%

age_years
Real number (ℝ)

Missing 

Distinct742
Distinct (%)7.8%
Missing1628
Missing (%)14.6%
Infinite0
Infinite (%)0.0%
Mean36.34819851
Minimum0
Maximum76
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:34.468113image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile21
Q128
median35
Q344
95-th percentile57
Maximum76
Range76
Interquartile range (IQR)16

Descriptive statistics

Standard deviation11.18592207
Coefficient of variation (CV)0.3077435065
Kurtosis-0.4755978254
Mean36.34819851
Median Absolute Deviation (MAD)8
Skewness0.5066850915
Sum344799.0111
Variance125.1248525
MonotonicityNot monotonic
2025-11-25T16:51:34.516760image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
31339
 
3.1%
30316
 
2.8%
28307
 
2.8%
26301
 
2.7%
34299
 
2.7%
29299
 
2.7%
33298
 
2.7%
25287
 
2.6%
37283
 
2.5%
24280
 
2.5%
Other values (732)6477
58.3%
(Missing)1628
 
14.6%
ValueCountFrequency (%)
01
 
< 0.1%
131
 
< 0.1%
142
 
< 0.1%
156
0.1%
164
< 0.1%
ValueCountFrequency (%)
761
< 0.1%
741
< 0.1%
722
< 0.1%
712
< 0.1%
701
< 0.1%

sex
Text

Missing 

Distinct4
Distinct (%)< 0.1%
Missing1333
Missing (%)12.0%
Memory size87.0 KiB
2025-11-25T16:51:34.554955image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length13
Median length7
Mean length5.119926388
Min length4

Characters and Unicode

Total characters50078
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowFemale
2nd rowFemale
3rd rowFemale
4th rowFemale
5th rowMale
ValueCountFrequency (%)
female4838
49.5%
male4519
46.2%
unknown423
 
4.3%
not1
 
< 0.1%
available1
 
< 0.1%
2025-11-25T16:51:34.625247image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e14196
28.3%
a9360
18.7%
l9359
18.7%
F4838
 
9.7%
m4838
 
9.7%
M4519
 
9.0%
n1269
 
2.5%
o424
 
0.8%
w423
 
0.8%
k423
 
0.8%
Other values (7)429
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter40296
80.5%
Uppercase Letter9781
 
19.5%
Space Separator1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e14196
35.2%
a9360
23.2%
l9359
23.2%
m4838
 
12.0%
n1269
 
3.1%
o424
 
1.1%
w423
 
1.0%
k423
 
1.0%
t1
 
< 0.1%
v1
 
< 0.1%
Other values (2)2
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
F4838
49.5%
M4519
46.2%
U423
 
4.3%
N1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin50077
> 99.9%
Common1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e14196
28.3%
a9360
18.7%
l9359
18.7%
F4838
 
9.7%
m4838
 
9.7%
M4519
 
9.0%
n1269
 
2.5%
o424
 
0.8%
w423
 
0.8%
k423
 
0.8%
Other values (6)428
 
0.9%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII50078
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e14196
28.3%
a9360
18.7%
l9359
18.7%
F4838
 
9.7%
m4838
 
9.7%
M4519
 
9.0%
n1269
 
2.5%
o424
 
0.8%
w423
 
0.8%
k423
 
0.8%
Other values (7)429
 
0.9%

race
Text

Missing 

Distinct7
Distinct (%)0.2%
Missing7148
Missing (%)64.3%
Memory size87.0 KiB
2025-11-25T16:51:34.660287image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length12
Median length5
Mean length5.246596067
Min length5

Characters and Unicode

Total characters20808
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowBlack
2nd rowBlack
3rd rowBlack
4th rowBlack
5th rowBlack
ValueCountFrequency (%)
black3132
78.9%
white320
 
8.1%
coloured315
 
7.9%
asian139
 
3.5%
other55
 
1.4%
not4
 
0.1%
reported4
 
0.1%
mixed1
 
< 0.1%
race1
 
< 0.1%
2025-11-25T16:51:34.740519image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l3447
16.6%
a3272
15.7%
c3133
15.1%
B3132
15.1%
k3132
15.1%
e700
 
3.4%
o638
 
3.1%
i460
 
2.2%
t383
 
1.8%
r378
 
1.8%
Other values (15)2133
10.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter16836
80.9%
Uppercase Letter3967
 
19.1%
Space Separator5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l3447
20.5%
a3272
19.4%
c3133
18.6%
k3132
18.6%
e700
 
4.2%
o638
 
3.8%
i460
 
2.7%
t383
 
2.3%
r378
 
2.2%
h375
 
2.2%
Other values (6)918
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
B3132
79.0%
W320
 
8.1%
C315
 
7.9%
A139
 
3.5%
O55
 
1.4%
N4
 
0.1%
M1
 
< 0.1%
R1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin20803
> 99.9%
Common5
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
l3447
16.6%
a3272
15.7%
c3133
15.1%
B3132
15.1%
k3132
15.1%
e700
 
3.4%
o638
 
3.1%
i460
 
2.2%
t383
 
1.8%
r378
 
1.8%
Other values (14)2128
10.2%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII20808
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l3447
16.6%
a3272
15.7%
c3133
15.1%
B3132
15.1%
k3132
15.1%
e700
 
3.4%
o638
 
3.1%
i460
 
2.2%
t383
 
1.8%
r378
 
1.8%
Other values (15)2133
10.3%

hiv_status
Text

Constant  Missing 

Distinct1
Distinct (%)< 0.1%
Missing4888
Missing (%)44.0%
Memory size87.0 KiB
2025-11-25T16:51:34.773551image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters49808
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPositive
2nd rowPositive
3rd rowPositive
4th rowPositive
5th rowPositive
ValueCountFrequency (%)
positive6226
100.0%
2025-11-25T16:51:34.850282image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i12452
25.0%
P6226
12.5%
o6226
12.5%
s6226
12.5%
t6226
12.5%
v6226
12.5%
e6226
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter43582
87.5%
Uppercase Letter6226
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i12452
28.6%
o6226
14.3%
s6226
14.3%
t6226
14.3%
v6226
14.3%
e6226
14.3%
Uppercase Letter
ValueCountFrequency (%)
P6226
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin49808
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i12452
25.0%
P6226
12.5%
o6226
12.5%
s6226
12.5%
t6226
12.5%
v6226
12.5%
e6226
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII49808
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i12452
25.0%
P6226
12.5%
o6226
12.5%
s6226
12.5%
t6226
12.5%
v6226
12.5%
e6226
12.5%

hiv_positive
Real number (ℝ)

Missing  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing427
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean0.5825769627
Minimum0
Maximum1
Zeros4461
Zeros (%)40.1%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:34.886512image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.4931569752
Coefficient of variation (CV)0.8465095718
Kurtosis-1.888159295
Mean0.5825769627
Median Absolute Deviation (MAD)0
Skewness-0.3349538724
Sum6226
Variance0.2432038022
MonotonicityNot monotonic
2025-11-25T16:51:34.920616image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
16226
56.0%
04461
40.1%
(Missing)427
 
3.8%
ValueCountFrequency (%)
04461
40.1%
16226
56.0%
ValueCountFrequency (%)
16226
56.0%
04461
40.1%

on_art
Real number (ℝ)

Constant  Missing 

Distinct1
Distinct (%)0.2%
Missing10637
Missing (%)95.7%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:34.954065image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum477
Variance0
MonotonicityIncreasing
2025-11-25T16:51:34.990967image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1477
 
4.3%
(Missing)10637
95.7%
ValueCountFrequency (%)
1477
4.3%
ValueCountFrequency (%)
1477
4.3%

virally_suppressed
Real number (ℝ)

Missing  Zeros 

Distinct2
Distinct (%)0.1%
Missing8593
Missing (%)77.3%
Infinite0
Infinite (%)0.0%
Mean0.1015470052
Minimum0
Maximum1
Zeros2265
Zeros (%)20.4%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:35.026913image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3021115942
Coefficient of variation (CV)2.975091129
Kurtosis4.972917106
Mean0.1015470052
Median Absolute Deviation (MAD)0
Skewness2.63988116
Sum256
Variance0.09127141535
MonotonicityNot monotonic
2025-11-25T16:51:35.060327image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
02265
 
20.4%
1256
 
2.3%
(Missing)8593
77.3%
ValueCountFrequency (%)
02265
20.4%
1256
 
2.3%
ValueCountFrequency (%)
1256
 
2.3%
02265
20.4%

cd4_count
Real number (ℝ)

Missing 

Distinct990
Distinct (%)21.7%
Missing6559
Missing (%)59.0%
Infinite0
Infinite (%)0.0%
Mean379.3506037
Minimum1
Maximum2703
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:35.100049image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile65
Q1199
median321
Q3509
95-th percentile875.9
Maximum2703
Range2702
Interquartile range (IQR)310

Descriptive statistics

Standard deviation260.3502105
Coefficient of variation (CV)0.6863049853
Kurtosis5.609918686
Mean379.3506037
Median Absolute Deviation (MAD)146
Skewness1.595998422
Sum1727942
Variance67782.23212
MonotonicityNot monotonic
2025-11-25T16:51:35.149702image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21518
 
0.2%
13817
 
0.2%
31517
 
0.2%
19516
 
0.1%
24416
 
0.1%
35015
 
0.1%
18215
 
0.1%
28814
 
0.1%
33614
 
0.1%
24214
 
0.1%
Other values (980)4399
39.6%
(Missing)6559
59.0%
ValueCountFrequency (%)
12
 
< 0.1%
23
< 0.1%
34
< 0.1%
42
 
< 0.1%
55
< 0.1%
ValueCountFrequency (%)
27031
< 0.1%
26092
< 0.1%
19961
< 0.1%
17811
< 0.1%
17251
< 0.1%

viral_load
Real number (ℝ)

Missing 

Distinct2153
Distinct (%)85.4%
Missing8594
Missing (%)77.3%
Infinite0
Infinite (%)0.0%
Mean2118245.258
Minimum0
Maximum96299000
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:35.197163image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16647.25
median39014.5
Q3158609.25
95-th percentile3134633.2
Maximum96299000
Range96299000
Interquartile range (IQR)151962

Descriptive statistics

Standard deviation10528497.2
Coefficient of variation (CV)4.970386296
Kurtosis42.14296949
Mean2118245.258
Median Absolute Deviation (MAD)38218.5
Skewness6.277623375
Sum5337978051
Variance1.108492534 × 1014
MonotonicityNot monotonic
2025-11-25T16:51:35.245012image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1244
 
2.2%
39553
 
< 0.1%
03
 
< 0.1%
839803
 
< 0.1%
63463
 
< 0.1%
100000003
 
< 0.1%
120493
 
< 0.1%
401523
 
< 0.1%
959000002
 
< 0.1%
5798742
 
< 0.1%
Other values (2143)2251
 
20.3%
(Missing)8594
77.3%
ValueCountFrequency (%)
03
 
< 0.1%
1244
2.2%
101
 
< 0.1%
311
 
< 0.1%
511
 
< 0.1%
ValueCountFrequency (%)
962990001
< 0.1%
959000002
< 0.1%
958130001
< 0.1%
951410001
< 0.1%
940250001
< 0.1%

viral_load_undetectable
Real number (ℝ)

Missing  Zeros 

Distinct2
Distinct (%)0.1%
Missing8594
Missing (%)77.3%
Infinite0
Infinite (%)0.0%
Mean0.09880952381
Minimum0
Maximum1
Zeros2271
Zeros (%)20.4%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:35.283115image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2984653274
Coefficient of variation (CV)3.020612952
Kurtosis5.24290207
Mean0.09880952381
Median Absolute Deviation (MAD)0
Skewness2.690490971
Sum249
Variance0.08908155164
MonotonicityNot monotonic
2025-11-25T16:51:35.315133image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
02271
 
20.4%
1249
 
2.2%
(Missing)8594
77.3%
ValueCountFrequency (%)
02271
20.4%
1249
 
2.2%
ValueCountFrequency (%)
1249
 
2.2%
02271
20.4%

log10_viral_load
Real number (ℝ)

Missing  Zeros 

Distinct2152
Distinct (%)85.5%
Missing8597
Missing (%)77.4%
Infinite0
Infinite (%)0.0%
Mean4.284449385
Minimum0
Maximum7.983621777
Zeros244
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:35.356812image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.825685708
median4.591798946
Q35.20068364
95-th percentile6.496806254
Maximum7.983621777
Range7.983621777
Interquartile range (IQR)1.374997932

Descriptive statistics

Standard deviation1.710838434
Coefficient of variation (CV)0.3993134894
Kurtosis1.611236419
Mean4.284449385
Median Absolute Deviation (MAD)0.6668480568
Skewness-1.118458906
Sum10783.9591
Variance2.926968147
MonotonicityNot monotonic
2025-11-25T16:51:35.406268image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0244
 
2.2%
73
 
< 0.1%
4.0809510043
 
< 0.1%
4.6037071833
 
< 0.1%
3.8025000683
 
< 0.1%
3.5971464883
 
< 0.1%
4.924175873
 
< 0.1%
4.7758579222
 
< 0.1%
3.6117233082
 
< 0.1%
4.7361892662
 
< 0.1%
Other values (2142)2249
 
20.2%
(Missing)8597
77.4%
ValueCountFrequency (%)
0244
2.2%
11
 
< 0.1%
1.4913616941
 
< 0.1%
1.7075701761
 
< 0.1%
1.869231721
 
< 0.1%
ValueCountFrequency (%)
7.9836217771
< 0.1%
7.9818186072
< 0.1%
7.9814244391
< 0.1%
7.9783677121
< 0.1%
7.9732433421
< 0.1%

viral_load_wrhi003_category
Real number (ℝ)

Missing  Zeros 

Distinct4
Distinct (%)1.8%
Missing10893
Missing (%)98.0%
Infinite0
Infinite (%)0.0%
Mean7.71040724
Minimum0
Maximum63
Zeros179
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:35.444507image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile40
Maximum63
Range63
Interquartile range (IQR)0

Descriptive statistics

Standard deviation16.02717381
Coefficient of variation (CV)2.078641674
Kurtosis0.8301934987
Mean7.71040724
Median Absolute Deviation (MAD)0
Skewness1.638382595
Sum1704
Variance256.8703003
MonotonicityNot monotonic
2025-11-25T16:51:35.477590image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
0179
 
1.6%
4040
 
0.4%
411
 
< 0.1%
631
 
< 0.1%
(Missing)10893
98.0%
ValueCountFrequency (%)
0179
1.6%
4040
 
0.4%
411
 
< 0.1%
631
 
< 0.1%
ValueCountFrequency (%)
631
 
< 0.1%
411
 
< 0.1%
4040
 
0.4%
0179
1.6%

hemoglobin
Real number (ℝ)

Missing 

Distinct119
Distinct (%)3.9%
Missing8078
Missing (%)72.7%
Infinite0
Infinite (%)0.0%
Mean12.80384387
Minimum5.2
Maximum20.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:35.519306image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum5.2
5-th percentile9.6
Q111.6
median12.9
Q314.1
95-th percentile15.8
Maximum20.5
Range15.3
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation1.900110813
Coefficient of variation (CV)0.1484015919
Kurtosis0.1431917951
Mean12.80384387
Median Absolute Deviation (MAD)1.2
Skewness-0.2093619526
Sum38872.47
Variance3.610421101
MonotonicityNot monotonic
2025-11-25T16:51:35.566482image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12187
 
1.7%
13143
 
1.3%
11139
 
1.3%
13.469
 
0.6%
1469
 
0.6%
13.366
 
0.6%
12.565
 
0.6%
14.161
 
0.5%
1061
 
0.5%
13.961
 
0.5%
Other values (109)2115
 
19.0%
(Missing)8078
72.7%
ValueCountFrequency (%)
5.21
< 0.1%
5.41
< 0.1%
6.11
< 0.1%
6.71
< 0.1%
6.81
< 0.1%
ValueCountFrequency (%)
20.51
 
< 0.1%
18.11
 
< 0.1%
183
< 0.1%
17.81
 
< 0.1%
17.72
< 0.1%

hematocrit
Real number (ℝ)

Missing 

Distinct299
Distinct (%)11.0%
Missing8397
Missing (%)75.6%
Infinite0
Infinite (%)0.0%
Mean38.63265366
Minimum10
Maximum60.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:35.614031image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile25
Q135
median39.5
Q343.5
95-th percentile50
Maximum60.3
Range50.3
Interquartile range (IQR)8.5

Descriptive statistics

Standard deviation7.768774811
Coefficient of variation (CV)0.2010934812
Kurtosis2.140797956
Mean38.63265366
Median Absolute Deviation (MAD)4.5
Skewness-0.9447946622
Sum104964.92
Variance60.35386206
MonotonicityNot monotonic
2025-11-25T16:51:35.740840image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40114
 
1.0%
45113
 
1.0%
42101
 
0.9%
4197
 
0.9%
4387
 
0.8%
3982
 
0.7%
3774
 
0.7%
4472
 
0.6%
3868
 
0.6%
3565
 
0.6%
Other values (289)1844
 
16.6%
(Missing)8397
75.6%
ValueCountFrequency (%)
1029
0.3%
132
 
< 0.1%
13.41
 
< 0.1%
144
 
< 0.1%
1539
0.4%
ValueCountFrequency (%)
60.31
 
< 0.1%
587
0.1%
577
0.1%
563
< 0.1%
55.91
 
< 0.1%

rbc_count
Real number (ℝ)

Missing 

Distinct258
Distinct (%)24.5%
Missing10062
Missing (%)90.5%
Infinite0
Infinite (%)0.0%
Mean4.689410646
Minimum2.86
Maximum7.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:35.786381image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum2.86
5-th percentile3.74
Q14.32
median4.68
Q35.0325
95-th percentile5.6545
Maximum7.2
Range4.34
Interquartile range (IQR)0.7125

Descriptive statistics

Standard deviation0.576375065
Coefficient of variation (CV)0.1229099152
Kurtosis0.4063149307
Mean4.689410646
Median Absolute Deviation (MAD)0.36
Skewness0.07349499925
Sum4933.26
Variance0.3322082156
MonotonicityNot monotonic
2025-11-25T16:51:35.832307image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.4514
 
0.1%
4.5414
 
0.1%
4.9814
 
0.1%
4.5813
 
0.1%
4.8412
 
0.1%
4.4412
 
0.1%
4.8812
 
0.1%
4.7211
 
0.1%
4.6811
 
0.1%
4.2711
 
0.1%
Other values (248)928
 
8.3%
(Missing)10062
90.5%
ValueCountFrequency (%)
2.861
< 0.1%
2.941
< 0.1%
3.132
< 0.1%
3.181
< 0.1%
3.191
< 0.1%
ValueCountFrequency (%)
7.21
< 0.1%
6.591
< 0.1%
6.451
< 0.1%
6.421
< 0.1%
6.361
< 0.1%

wbc_count
Real number (ℝ)

Missing 

Distinct578
Distinct (%)19.1%
Missing8087
Missing (%)72.8%
Infinite0
Infinite (%)0.0%
Mean4.711377602
Minimum1.2
Maximum24.68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:35.876009image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1.2
5-th percentile2.5
Q13.5
median4.4
Q35.55
95-th percentile7.907
Maximum24.68
Range23.48
Interquartile range (IQR)2.05

Descriptive statistics

Standard deviation1.776204855
Coefficient of variation (CV)0.3770032897
Kurtosis9.348479204
Mean4.711377602
Median Absolute Deviation (MAD)1
Skewness1.843309166
Sum14261.34
Variance3.154903687
MonotonicityNot monotonic
2025-11-25T16:51:35.921324image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.369
 
0.6%
3.768
 
0.6%
3.867
 
0.6%
3.964
 
0.6%
3.663
 
0.6%
462
 
0.6%
4.361
 
0.5%
3.260
 
0.5%
4.260
 
0.5%
4.556
 
0.5%
Other values (568)2397
 
21.6%
(Missing)8087
72.8%
ValueCountFrequency (%)
1.23
< 0.1%
1.31
 
< 0.1%
1.51
 
< 0.1%
1.521
 
< 0.1%
1.65
< 0.1%
ValueCountFrequency (%)
24.681
< 0.1%
17.961
< 0.1%
15.851
< 0.1%
15.781
< 0.1%
15.331
< 0.1%

platelet_count
Real number (ℝ)

Missing 

Distinct392
Distinct (%)16.9%
Missing8792
Missing (%)79.1%
Infinite0
Infinite (%)0.0%
Mean250.0633075
Minimum24
Maximum884
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:35.965020image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum24
5-th percentile141
Q1197
median240
Q3289
95-th percentile397
Maximum884
Range860
Interquartile range (IQR)92

Descriptive statistics

Standard deviation81.86342199
Coefficient of variation (CV)0.3273707879
Kurtosis4.176287622
Mean250.0633075
Median Absolute Deviation (MAD)46
Skewness1.193485764
Sum580647
Variance6701.619859
MonotonicityNot monotonic
2025-11-25T16:51:36.008889image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21321
 
0.2%
23220
 
0.2%
24020
 
0.2%
22719
 
0.2%
26718
 
0.2%
26918
 
0.2%
22218
 
0.2%
21918
 
0.2%
20517
 
0.2%
21217
 
0.2%
Other values (382)2136
 
19.2%
(Missing)8792
79.1%
ValueCountFrequency (%)
241
< 0.1%
361
< 0.1%
381
< 0.1%
421
< 0.1%
441
< 0.1%
ValueCountFrequency (%)
8841
< 0.1%
7511
< 0.1%
7471
< 0.1%
6761
< 0.1%
6521
< 0.1%

mcv
Real number (ℝ)

Missing 

Distinct286
Distinct (%)27.2%
Missing10062
Missing (%)90.5%
Infinite0
Infinite (%)0.0%
Mean86.90522814
Minimum58.1
Maximum103.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:36.053492image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum58.1
5-th percentile73.455
Q183.6
median87.5
Q391.7
95-th percentile96.445
Maximum103.5
Range45.4
Interquartile range (IQR)8.1

Descriptive statistics

Standard deviation6.948635886
Coefficient of variation (CV)0.07995647713
Kurtosis1.409964815
Mean86.90522814
Median Absolute Deviation (MAD)4
Skewness-0.8789278222
Sum91424.3
Variance48.28354067
MonotonicityNot monotonic
2025-11-25T16:51:36.103459image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
84.513
 
0.1%
87.313
 
0.1%
8812
 
0.1%
89.312
 
0.1%
90.411
 
0.1%
85.210
 
0.1%
86.910
 
0.1%
84.710
 
0.1%
91.810
 
0.1%
89.110
 
0.1%
Other values (276)941
 
8.5%
(Missing)10062
90.5%
ValueCountFrequency (%)
58.11
< 0.1%
59.71
< 0.1%
601
< 0.1%
60.11
< 0.1%
60.91
< 0.1%
ValueCountFrequency (%)
103.52
< 0.1%
102.31
< 0.1%
101.81
< 0.1%
100.81
< 0.1%
100.71
< 0.1%

mch
Real number (ℝ)

Missing 

Distinct138
Distinct (%)13.1%
Missing10062
Missing (%)90.5%
Infinite0
Infinite (%)0.0%
Mean28.41159696
Minimum16.7
Maximum34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:36.149357image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum16.7
5-th percentile23.1
Q127.1
median28.7
Q330.3
95-th percentile32.145
Maximum34
Range17.3
Interquartile range (IQR)3.2

Descriptive statistics

Standard deviation2.724878949
Coefficient of variation (CV)0.09590727875
Kurtosis1.480215606
Mean28.41159696
Median Absolute Deviation (MAD)1.6
Skewness-0.9443723704
Sum29889
Variance7.424965287
MonotonicityNot monotonic
2025-11-25T16:51:36.197111image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28.625
 
0.2%
29.921
 
0.2%
28.821
 
0.2%
28.921
 
0.2%
27.920
 
0.2%
29.420
 
0.2%
27.519
 
0.2%
27.318
 
0.2%
27.218
 
0.2%
3018
 
0.2%
Other values (128)851
 
7.7%
(Missing)10062
90.5%
ValueCountFrequency (%)
16.71
< 0.1%
17.31
< 0.1%
17.61
< 0.1%
17.81
< 0.1%
17.91
< 0.1%
ValueCountFrequency (%)
341
 
< 0.1%
33.91
 
< 0.1%
33.82
< 0.1%
33.71
 
< 0.1%
33.53
< 0.1%

mchc
Real number (ℝ)

Missing 

Distinct59
Distinct (%)5.6%
Missing10062
Missing (%)90.5%
Infinite0
Infinite (%)0.0%
Mean32.65370722
Minimum28.3
Maximum35.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:36.247095image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum28.3
5-th percentile31.2
Q132.2
median32.7
Q333.2
95-th percentile33.9
Maximum35.9
Range7.6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.8926571917
Coefficient of variation (CV)0.02733708567
Kurtosis2.027430734
Mean32.65370722
Median Absolute Deviation (MAD)0.5
Skewness-0.5820963288
Sum34351.7
Variance0.7968368619
MonotonicityNot monotonic
2025-11-25T16:51:36.298419image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32.660
 
0.5%
32.757
 
0.5%
33.154
 
0.5%
32.454
 
0.5%
3353
 
0.5%
33.252
 
0.5%
32.551
 
0.5%
32.850
 
0.4%
32.946
 
0.4%
32.344
 
0.4%
Other values (49)531
 
4.8%
(Missing)10062
90.5%
ValueCountFrequency (%)
28.31
< 0.1%
28.61
< 0.1%
28.71
< 0.1%
28.81
< 0.1%
29.32
< 0.1%
ValueCountFrequency (%)
35.91
 
< 0.1%
35.61
 
< 0.1%
35.31
 
< 0.1%
352
< 0.1%
34.94
< 0.1%

rdw
Real number (ℝ)

Missing 

Distinct58
Distinct (%)26.7%
Missing10897
Missing (%)98.0%
Infinite0
Infinite (%)0.0%
Mean14.6281106
Minimum11.9
Maximum23.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:36.348785image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum11.9
5-th percentile12.6
Q113.5
median14.3
Q315.1
95-th percentile18.34
Maximum23.9
Range12
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation1.805263043
Coefficient of variation (CV)0.123410541
Kurtosis5.632496659
Mean14.6281106
Median Absolute Deviation (MAD)0.8
Skewness2.035827813
Sum3174.3
Variance3.258974654
MonotonicityNot monotonic
2025-11-25T16:51:36.396220image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13.812
 
0.1%
14.311
 
0.1%
14.110
 
0.1%
13.310
 
0.1%
14.29
 
0.1%
15.28
 
0.1%
13.98
 
0.1%
13.48
 
0.1%
158
 
0.1%
14.97
 
0.1%
Other values (48)126
 
1.1%
(Missing)10897
98.0%
ValueCountFrequency (%)
11.91
 
< 0.1%
12.13
< 0.1%
12.21
 
< 0.1%
12.41
 
< 0.1%
12.53
< 0.1%
ValueCountFrequency (%)
23.91
< 0.1%
21.91
< 0.1%
20.82
< 0.1%
20.51
< 0.1%
201
< 0.1%

neutrophils_pct
Real number (ℝ)

Missing 

Distinct442
Distinct (%)34.5%
Missing9831
Missing (%)88.5%
Infinite0
Infinite (%)0.0%
Mean5.166849571
Minimum0.39
Maximum71.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:36.444712image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.39
5-th percentile0.861
Q11.38
median1.93
Q32.79
95-th percentile40.05
Maximum71.1
Range70.71
Interquartile range (IQR)1.41

Descriptive statistics

Standard deviation11.96311081
Coefficient of variation (CV)2.315358837
Kurtosis13.58850286
Mean5.166849571
Median Absolute Deviation (MAD)0.63
Skewness3.802643735
Sum6629.068
Variance143.1160203
MonotonicityNot monotonic
2025-11-25T16:51:36.494357image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.1512
 
0.1%
1.4412
 
0.1%
1.3911
 
0.1%
1.5811
 
0.1%
1.4210
 
0.1%
1.6210
 
0.1%
1.5210
 
0.1%
1.8410
 
0.1%
1.289
 
0.1%
1.79
 
0.1%
Other values (432)1179
 
10.6%
(Missing)9831
88.5%
ValueCountFrequency (%)
0.391
< 0.1%
0.451
< 0.1%
0.461
< 0.1%
0.511
< 0.1%
0.531
< 0.1%
ValueCountFrequency (%)
71.11
< 0.1%
70.82
< 0.1%
70.71
< 0.1%
70.51
< 0.1%
69.51
< 0.1%

lymphocytes_pct
Real number (ℝ)

Missing 

Distinct367
Distinct (%)28.6%
Missing9831
Missing (%)88.5%
Infinite0
Infinite (%)0.0%
Mean3.837404521
Minimum0.25
Maximum53.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:36.542663image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.25
5-th percentile0.81
Q11.25
median1.7
Q32.28
95-th percentile26.64
Maximum53.1
Range52.85
Interquartile range (IQR)1.03

Descriptive statistics

Standard deviation8.239678262
Coefficient of variation (CV)2.147200853
Kurtosis14.37978476
Mean3.837404521
Median Absolute Deviation (MAD)0.5
Skewness3.900937216
Sum4923.39
Variance67.89229786
MonotonicityNot monotonic
2025-11-25T16:51:36.592896image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.2915
 
0.1%
1.1213
 
0.1%
1.7613
 
0.1%
1.4213
 
0.1%
1.4312
 
0.1%
1.8212
 
0.1%
1.2512
 
0.1%
1.3312
 
0.1%
1.0811
 
0.1%
1.4411
 
0.1%
Other values (357)1159
 
10.4%
(Missing)9831
88.5%
ValueCountFrequency (%)
0.251
< 0.1%
0.321
< 0.1%
0.342
< 0.1%
0.351
< 0.1%
0.362
< 0.1%
ValueCountFrequency (%)
53.11
< 0.1%
52.21
< 0.1%
51.11
< 0.1%
49.51
< 0.1%
47.81
< 0.1%

monocytes_pct
Real number (ℝ)

Missing 

Distinct55
Distinct (%)25.3%
Missing10897
Missing (%)98.0%
Infinite0
Infinite (%)0.0%
Mean0.4068663594
Minimum0.14
Maximum0.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:36.639496image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.14
5-th percentile0.208
Q10.32
median0.39
Q30.48
95-th percentile0.632
Maximum0.94
Range0.8
Interquartile range (IQR)0.16

Descriptive statistics

Standard deviation0.1320611027
Coefficient of variation (CV)0.3245810316
Kurtosis1.267488033
Mean0.4068663594
Median Absolute Deviation (MAD)0.08
Skewness0.7283666223
Sum88.29
Variance0.01744013484
MonotonicityNot monotonic
2025-11-25T16:51:36.691291image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.3812
 
0.1%
0.3712
 
0.1%
0.3510
 
0.1%
0.348
 
0.1%
0.368
 
0.1%
0.438
 
0.1%
0.486
 
0.1%
0.396
 
0.1%
0.46
 
0.1%
0.316
 
0.1%
Other values (45)135
 
1.2%
(Missing)10897
98.0%
ValueCountFrequency (%)
0.141
 
< 0.1%
0.161
 
< 0.1%
0.182
< 0.1%
0.194
< 0.1%
0.23
< 0.1%
ValueCountFrequency (%)
0.941
< 0.1%
0.911
< 0.1%
0.721
< 0.1%
0.712
< 0.1%
0.72
< 0.1%

eosinophils_pct
Real number (ℝ)

Missing 

Distinct47
Distinct (%)21.7%
Missing10897
Missing (%)98.0%
Infinite0
Infinite (%)0.0%
Mean0.1341474654
Minimum0
Maximum0.74
Zeros5
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:36.741630image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.02
Q10.05
median0.1
Q30.18
95-th percentile0.38
Maximum0.74
Range0.74
Interquartile range (IQR)0.13

Descriptive statistics

Standard deviation0.1335079981
Coefficient of variation (CV)0.9952331017
Kurtosis5.742391001
Mean0.1341474654
Median Absolute Deviation (MAD)0.06
Skewness2.208557949
Sum29.11
Variance0.01782438556
MonotonicityNot monotonic
2025-11-25T16:51:36.791543image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0.0418
 
0.2%
0.0717
 
0.2%
0.115
 
0.1%
0.0515
 
0.1%
0.0315
 
0.1%
0.0211
 
0.1%
0.1210
 
0.1%
0.1110
 
0.1%
0.0610
 
0.1%
0.088
 
0.1%
Other values (37)88
 
0.8%
(Missing)10897
98.0%
ValueCountFrequency (%)
05
 
< 0.1%
0.013
 
< 0.1%
0.0211
0.1%
0.0315
0.1%
0.0418
0.2%
ValueCountFrequency (%)
0.741
< 0.1%
0.71
< 0.1%
0.681
< 0.1%
0.651
< 0.1%
0.621
< 0.1%

basophils_pct
Real number (ℝ)

Missing 

Distinct14
Distinct (%)6.5%
Missing10897
Missing (%)98.0%
Infinite0
Infinite (%)0.0%
Mean0.03170506912
Minimum0
Maximum0.19
Zeros13
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:36.832413image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.02
median0.03
Q30.04
95-th percentile0.07
Maximum0.19
Range0.19
Interquartile range (IQR)0.02

Descriptive statistics

Standard deviation0.02421634018
Coefficient of variation (CV)0.7638002643
Kurtosis11.40330028
Mean0.03170506912
Median Absolute Deviation (MAD)0.01
Skewness2.550673951
Sum6.88
Variance0.0005864311316
MonotonicityNot monotonic
2025-11-25T16:51:36.871274image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0.0258
 
0.5%
0.0348
 
0.4%
0.0429
 
0.3%
0.0127
 
0.2%
0.0518
 
0.2%
013
 
0.1%
0.0610
 
0.1%
0.077
 
0.1%
0.122
 
< 0.1%
0.111
 
< 0.1%
Other values (4)4
 
< 0.1%
(Missing)10897
98.0%
ValueCountFrequency (%)
013
 
0.1%
0.0127
0.2%
0.0258
0.5%
0.0348
0.4%
0.0429
0.3%
ValueCountFrequency (%)
0.191
< 0.1%
0.151
< 0.1%
0.122
< 0.1%
0.111
< 0.1%
0.091
< 0.1%

fasting_glucose
Real number (ℝ)

Missing 

Distinct696
Distinct (%)25.1%
Missing8346
Missing (%)75.1%
Infinite0
Infinite (%)0.0%
Mean89.19807169
Minimum36.396764
Maximum535.68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:36.997323image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum36.396764
5-th percentile66.6
Q177.194474
median84.73277
Q394.68
95-th percentile115.1777043
Maximum535.68
Range499.283236
Interquartile range (IQR)17.485526

Descriptive statistics

Standard deviation28.99683656
Coefficient of variation (CV)0.3250836706
Kurtosis73.69329041
Mean89.19807169
Median Absolute Deviation (MAD)8.73277
Skewness6.993098302
Sum246900.2624
Variance840.8165303
MonotonicityNot monotonic
2025-11-25T16:51:37.042253image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
77.472
 
0.6%
8166
 
0.6%
79.266
 
0.6%
7261
 
0.5%
73.852
 
0.5%
75.649
 
0.4%
84.646
 
0.4%
82.845
 
0.4%
86.439
 
0.4%
9033
 
0.3%
Other values (686)2239
 
20.1%
(Missing)8346
75.1%
ValueCountFrequency (%)
36.3967641
< 0.1%
36.7571281
< 0.1%
39.8202221
< 0.1%
40.0004041
< 0.1%
40.7211321
< 0.1%
ValueCountFrequency (%)
535.681
< 0.1%
486.49141
< 0.1%
477.24363091
< 0.1%
444.77807781
< 0.1%
363.781
< 0.1%

log10_fasting_glucose
Real number (ℝ)

Missing 

Distinct696
Distinct (%)25.1%
Missing8346
Missing (%)75.1%
Infinite0
Infinite (%)0.0%
Mean1.937789821
Minimum1.561062773
Maximum2.728905432
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:37.087284image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1.561062773
5-th percentile1.823474229
Q11.887586141
median1.928051337
Q31.976258249
95-th percentile2.061368403
Maximum2.728905432
Range1.167842659
Interquartile range (IQR)0.08867210823

Descriptive statistics

Standard deviation0.09405172692
Coefficient of variation (CV)0.04853556661
Kurtosis13.42853196
Mean1.937789821
Median Absolute Deviation (MAD)0.0440588917
Skewness2.315213878
Sum5363.802224
Variance0.008845727338
MonotonicityNot monotonic
2025-11-25T16:51:37.134403image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.88874096172
 
0.6%
1.90848501966
 
0.6%
1.89872518266
 
0.6%
1.85733249661
 
0.5%
1.86805636252
 
0.5%
1.87852179649
 
0.4%
1.92737036346
 
0.4%
1.91803033745
 
0.4%
1.93651374239
 
0.4%
1.95424250933
 
0.3%
Other values (686)2239
 
20.1%
(Missing)8346
75.1%
ValueCountFrequency (%)
1.5610627731
< 0.1%
1.5653415711
< 0.1%
1.6001036771
< 0.1%
1.6020643781
< 0.1%
1.6098198421
< 0.1%
ValueCountFrequency (%)
2.7289054321
< 0.1%
2.6870751671
< 0.1%
2.6787401411
< 0.1%
2.6481433741
< 0.1%
2.5608388191
< 0.1%

total_cholesterol
Real number (ℝ)

Missing 

Distinct826
Distinct (%)27.8%
Missing8145
Missing (%)73.3%
Infinite0
Infinite (%)0.0%
Mean158.7243819
Minimum57.78
Maximum463.2666
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:37.179851image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum57.78
5-th percentile101.3154
Q1131.478
median155.4534
Q3182.9091
95-th percentile225.4461
Maximum463.2666
Range405.4866
Interquartile range (IQR)51.4311

Descriptive statistics

Standard deviation38.59061119
Coefficient of variation (CV)0.243129699
Kurtosis1.446416548
Mean158.7243819
Median Absolute Deviation (MAD)25.8334
Skewness0.6330078493
Sum471252.6898
Variance1489.235272
MonotonicityNot monotonic
2025-11-25T16:51:37.228768image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
143.07953
 
0.5%
158.54739
 
0.4%
123.74438
 
0.3%
154.6837
 
0.3%
166.28136
 
0.3%
135.34534
 
0.3%
146.94633
 
0.3%
127.61132
 
0.3%
170.14831
 
0.3%
139.21230
 
0.3%
Other values (816)2606
 
23.4%
(Missing)8145
73.3%
ValueCountFrequency (%)
57.781
 
< 0.1%
61.8721
 
< 0.1%
65.891
 
< 0.1%
69.6063
< 0.1%
70.37941
 
< 0.1%
ValueCountFrequency (%)
463.26661
< 0.1%
316.32061
< 0.1%
302.39941
< 0.1%
298.14571
< 0.1%
293.8921
< 0.1%

hdl_cholesterol
Real number (ℝ)

Missing 

Distinct570
Distinct (%)19.2%
Missing8152
Missing (%)73.3%
Infinite0
Infinite (%)0.0%
Mean44.68890105
Minimum10.8276
Maximum143.079
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:37.277274image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum10.8276
5-th percentile24.3621
Q134.803
median42.537
Q352.5912
95-th percentile71.9262
Maximum143.079
Range132.2514
Interquartile range (IQR)17.7882

Descriptive statistics

Standard deviation15.36030714
Coefficient of variation (CV)0.3437163765
Kurtosis5.002386641
Mean44.68890105
Median Absolute Deviation (MAD)8.5074
Skewness1.452912412
Sum132368.5249
Variance235.9390354
MonotonicityNot monotonic
2025-11-25T16:51:37.325750image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42.537117
 
1.1%
34.803105
 
0.9%
38.6792
 
0.8%
30.93670
 
0.6%
46.40470
 
0.6%
54.13868
 
0.6%
50.27153
 
0.5%
27.06951
 
0.5%
58.00540
 
0.4%
40.216835
 
0.3%
Other values (560)2261
 
20.3%
(Missing)8152
73.3%
ValueCountFrequency (%)
10.82761
 
< 0.1%
12.37444
< 0.1%
13.14784
< 0.1%
151
 
< 0.1%
15.08133
< 0.1%
ValueCountFrequency (%)
143.0796
0.1%
125.29081
 
< 0.1%
121.42381
 
< 0.1%
121.03711
 
< 0.1%
120.26371
 
< 0.1%

ldl_cholesterol
Real number (ℝ)

Missing 

Distinct799
Distinct (%)27.2%
Missing8174
Missing (%)73.5%
Infinite0
Infinite (%)0.0%
Mean89.99757406
Minimum4.87002
Maximum376.6458
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:37.371158image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum4.87002
5-th percentile35.9631
Q163.0321
median88.1676
Q3112.9164
95-th percentile152.753675
Maximum376.6458
Range371.77578
Interquartile range (IQR)49.8843

Descriptive statistics

Standard deviation36.0601791
Coefficient of variation (CV)0.400679457
Kurtosis1.058690249
Mean89.99757406
Median Absolute Deviation (MAD)24.825
Skewness0.5430161309
Sum264592.8677
Variance1300.336517
MonotonicityNot monotonic
2025-11-25T16:51:37.418285image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
104.40949
 
0.4%
88.94140
 
0.4%
65.73938
 
0.3%
81.20735
 
0.3%
77.3433
 
0.3%
85.07432
 
0.3%
108.27632
 
0.3%
73.47332
 
0.3%
69.60631
 
0.3%
92.80831
 
0.3%
Other values (789)2587
 
23.3%
(Missing)8174
73.5%
ValueCountFrequency (%)
4.870021
< 0.1%
5.220961
< 0.1%
6.654121
< 0.1%
8.000381
< 0.1%
9.221981
< 0.1%
ValueCountFrequency (%)
376.64581
< 0.1%
215.39191
< 0.1%
214.61851
< 0.1%
207.27121
< 0.1%
202.24411
< 0.1%

triglycerides
Real number (ℝ)

Missing 

Distinct207
Distinct (%)21.3%
Missing10142
Missing (%)91.3%
Infinite0
Infinite (%)0.0%
Mean92.23490267
Minimum19.4854
Maximum922.8994
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:37.465428image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum19.4854
5-th percentile37.1994
Q156.6848
median75.2845
Q3107.1697
95-th percentile190.824065
Maximum922.8994
Range903.414
Interquartile range (IQR)50.4849

Descriptive statistics

Standard deviation65.85198381
Coefficient of variation (CV)0.7139594871
Kurtosis38.23901069
Mean92.23490267
Median Absolute Deviation (MAD)22.58535
Skewness4.666526795
Sum89652.3254
Variance4336.483771
MonotonicityNot monotonic
2025-11-25T16:51:37.509740image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
72.627417
 
0.2%
71.741717
 
0.2%
62.884716
 
0.1%
58.456216
 
0.1%
61.113315
 
0.1%
47.827814
 
0.1%
73.513114
 
0.1%
69.970313
 
0.1%
69.084613
 
0.1%
57.570513
 
0.1%
Other values (197)824
 
7.4%
(Missing)10142
91.3%
ValueCountFrequency (%)
19.48541
< 0.1%
22.14251
< 0.1%
24.79961
< 0.1%
26.5712
< 0.1%
28.34242
< 0.1%
ValueCountFrequency (%)
922.89941
< 0.1%
641.24681
< 0.1%
495.9922
< 0.1%
482.70651
< 0.1%
464.10681
< 0.1%

creatinine
Real number (ℝ)

Missing 

Distinct159
Distinct (%)12.7%
Missing9862
Missing (%)88.7%
Infinite0
Infinite (%)0.0%
Mean0.761424472
Minimum0.350678733
Maximum2.680995475
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:37.552946image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.350678733
5-th percentile0.5090497738
Q10.6334841629
median0.73
Q30.86
95-th percentile1.085972851
Maximum2.680995475
Range2.330316742
Interquartile range (IQR)0.2265158371

Descriptive statistics

Standard deviation0.189627816
Coefficient of variation (CV)0.2490435007
Kurtosis12.02938179
Mean0.761424472
Median Absolute Deviation (MAD)0.1089140271
Skewness1.89141218
Sum953.3034389
Variance0.0359587086
MonotonicityNot monotonic
2025-11-25T16:51:37.599681image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.833
 
0.3%
0.712669683332
 
0.3%
0.735294117631
 
0.3%
0.633484162928
 
0.3%
0.588235294127
 
0.2%
0.610859728527
 
0.2%
0.723981900526
 
0.2%
0.690045248923
 
0.2%
0.644796380123
 
0.2%
0.723
 
0.2%
Other values (149)979
 
8.8%
(Missing)9862
88.7%
ValueCountFrequency (%)
0.3506787332
< 0.1%
0.38461538461
< 0.1%
0.4072398191
< 0.1%
0.41855203621
< 0.1%
0.422
< 0.1%
ValueCountFrequency (%)
2.6809954751
< 0.1%
2.241
< 0.1%
1.9117647061
< 0.1%
1.4592760182
< 0.1%
1.451
< 0.1%

creatinine_clearance
Real number (ℝ)

Missing 

Distinct113
Distinct (%)51.1%
Missing10893
Missing (%)98.0%
Infinite0
Infinite (%)0.0%
Mean129.1809955
Minimum40
Maximum243
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:37.646078image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile78
Q1100
median126
Q3154
95-th percentile191
Maximum243
Range203
Interquartile range (IQR)54

Descriptive statistics

Standard deviation37.49925819
Coefficient of variation (CV)0.2902846355
Kurtosis-0.3834413189
Mean129.1809955
Median Absolute Deviation (MAD)27
Skewness0.3584882393
Sum28549
Variance1406.194364
MonotonicityNot monotonic
2025-11-25T16:51:37.696899image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1307
 
0.1%
1275
 
< 0.1%
905
 
< 0.1%
935
 
< 0.1%
1005
 
< 0.1%
945
 
< 0.1%
1205
 
< 0.1%
864
 
< 0.1%
1194
 
< 0.1%
1354
 
< 0.1%
Other values (103)172
 
1.5%
(Missing)10893
98.0%
ValueCountFrequency (%)
401
< 0.1%
591
< 0.1%
601
< 0.1%
642
< 0.1%
652
< 0.1%
ValueCountFrequency (%)
2431
< 0.1%
2251
< 0.1%
2171
< 0.1%
2091
< 0.1%
2051
< 0.1%

bun
Real number (ℝ)

Missing 

Distinct46
Distinct (%)51.1%
Missing11024
Missing (%)99.2%
Infinite0
Infinite (%)0.0%
Mean62.88888889
Minimum31
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:37.743692image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile42
Q156
median62
Q370.75
95-th percentile84.1
Maximum90
Range59
Interquartile range (IQR)14.75

Descriptive statistics

Standard deviation12.2597766
Coefficient of variation (CV)0.1949434442
Kurtosis-0.005287437343
Mean62.88888889
Median Absolute Deviation (MAD)7.5
Skewness-0.009260263402
Sum5660
Variance150.3021223
MonotonicityNot monotonic
2025-11-25T16:51:37.788420image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
646
 
0.1%
626
 
0.1%
585
 
< 0.1%
595
 
< 0.1%
714
 
< 0.1%
703
 
< 0.1%
563
 
< 0.1%
553
 
< 0.1%
523
 
< 0.1%
423
 
< 0.1%
Other values (36)49
 
0.4%
(Missing)11024
99.2%
ValueCountFrequency (%)
311
 
< 0.1%
351
 
< 0.1%
411
 
< 0.1%
423
< 0.1%
431
 
< 0.1%
ValueCountFrequency (%)
901
< 0.1%
891
< 0.1%
881
< 0.1%
871
< 0.1%
851
< 0.1%

alt
Real number (ℝ)

Missing 

Distinct95
Distinct (%)5.6%
Missing9422
Missing (%)84.8%
Infinite0
Infinite (%)0.0%
Mean18.28427896
Minimum1
Maximum284
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:37.833178image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11.75
median16
Q324
95-th percentile46.45
Maximum284
Range283
Interquartile range (IQR)22.25

Descriptive statistics

Standard deviation21.18547897
Coefficient of variation (CV)1.15867183
Kurtosis45.92689112
Mean18.28427896
Median Absolute Deviation (MAD)9
Skewness5.136662082
Sum30937
Variance448.8245191
MonotonicityNot monotonic
2025-11-25T16:51:37.878666image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1423
 
3.8%
1477
 
0.7%
1566
 
0.6%
1764
 
0.6%
1660
 
0.5%
2059
 
0.5%
1859
 
0.5%
1355
 
0.5%
2155
 
0.5%
1251
 
0.5%
Other values (85)723
 
6.5%
(Missing)9422
84.8%
ValueCountFrequency (%)
1423
3.8%
215
 
0.1%
51
 
< 0.1%
65
 
< 0.1%
716
 
0.1%
ValueCountFrequency (%)
2841
< 0.1%
2671
< 0.1%
2401
< 0.1%
2341
< 0.1%
1771
< 0.1%

ast
Real number (ℝ)

Missing 

Distinct253
Distinct (%)15.1%
Missing9437
Missing (%)84.9%
Infinite0
Infinite (%)0.0%
Mean37.65074538
Minimum10
Maximum263
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:37.925567image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile17
Q123
median30
Q350
95-th percentile71.52
Maximum263
Range253
Interquartile range (IQR)27

Descriptive statistics

Standard deviation22.23621817
Coefficient of variation (CV)0.5905917119
Kurtosis19.49004295
Mean37.65074538
Median Absolute Deviation (MAD)10
Skewness3.048433977
Sum63140.3
Variance494.4493983
MonotonicityNot monotonic
2025-11-25T16:51:37.974103image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2276
 
0.7%
2470
 
0.6%
2369
 
0.6%
2566
 
0.6%
2065
 
0.6%
2660
 
0.5%
1959
 
0.5%
2156
 
0.5%
2750
 
0.4%
1849
 
0.4%
Other values (243)1057
 
9.5%
(Missing)9437
84.9%
ValueCountFrequency (%)
101
 
< 0.1%
11.12
 
< 0.1%
125
< 0.1%
133
 
< 0.1%
1411
0.1%
ValueCountFrequency (%)
2631
< 0.1%
2451
< 0.1%
2181
< 0.1%
1961
< 0.1%
1921
< 0.1%

alp
Real number (ℝ)

Missing 

Distinct139
Distinct (%)13.5%
Missing10083
Missing (%)90.7%
Infinite0
Infinite (%)0.0%
Mean81.8186227
Minimum30
Maximum946
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:38.021555image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile45.5
Q160
median74
Q392
95-th percentile139
Maximum946
Range916
Interquartile range (IQR)32

Descriptive statistics

Standard deviation45.21769439
Coefficient of variation (CV)0.5526577312
Kurtosis139.8851272
Mean81.8186227
Median Absolute Deviation (MAD)16
Skewness8.743455393
Sum84355
Variance2044.639886
MonotonicityNot monotonic
2025-11-25T16:51:38.069339image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6225
 
0.2%
7725
 
0.2%
6123
 
0.2%
6622
 
0.2%
7221
 
0.2%
7620
 
0.2%
5520
 
0.2%
8520
 
0.2%
6820
 
0.2%
5319
 
0.2%
Other values (129)816
 
7.3%
(Missing)10083
90.7%
ValueCountFrequency (%)
302
< 0.1%
312
< 0.1%
322
< 0.1%
332
< 0.1%
341
< 0.1%
ValueCountFrequency (%)
9461
< 0.1%
4831
< 0.1%
3741
< 0.1%
3671
< 0.1%
3601
< 0.1%

total_bilirubin
Real number (ℝ)

Missing 

Distinct128
Distinct (%)12.4%
Missing10083
Missing (%)90.7%
Infinite0
Infinite (%)0.0%
Mean1.35837006
Minimum0.1
Maximum5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:38.115699image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.2
Q10.3567251462
median0.5
Q32.4
95-th percentile4.6
Maximum5
Range4.9
Interquartile range (IQR)2.043274854

Descriptive statistics

Standard deviation1.532920344
Coefficient of variation (CV)1.128499802
Kurtosis-0.1606917024
Mean1.35837006
Median Absolute Deviation (MAD)0.2
Skewness1.22210338
Sum1400.479532
Variance2.34984478
MonotonicityNot monotonic
2025-11-25T16:51:38.166318image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.493
 
0.8%
0.393
 
0.8%
0.564
 
0.6%
0.255
 
0.5%
0.646
 
0.4%
0.733
 
0.3%
0.818
 
0.2%
4.118
 
0.2%
4.917
 
0.2%
4.614
 
0.1%
Other values (118)580
 
5.2%
(Missing)10083
90.7%
ValueCountFrequency (%)
0.15
 
< 0.1%
0.255
0.5%
0.29824561414
 
0.1%
0.393
0.8%
0.304093567312
 
0.1%
ValueCountFrequency (%)
512
0.1%
4.917
0.2%
4.88
0.1%
4.712
0.1%
4.614
0.1%

albumin
Real number (ℝ)

Missing 

Distinct176
Distinct (%)8.9%
Missing9142
Missing (%)82.3%
Infinite0
Infinite (%)0.0%
Mean4.112555781
Minimum1.7
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:38.218785image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1.7
5-th percentile3.4
Q13.9
median4.125
Q34.35
95-th percentile4.7
Maximum6
Range4.3
Interquartile range (IQR)0.45

Descriptive statistics

Standard deviation0.3962676701
Coefficient of variation (CV)0.09635557333
Kurtosis2.5689115
Mean4.112555781
Median Absolute Deviation (MAD)0.225
Skewness-0.5417574114
Sum8109.96
Variance0.1570280664
MonotonicityNot monotonic
2025-11-25T16:51:38.352817image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.1185
 
1.7%
4.3179
 
1.6%
4.2163
 
1.5%
4142
 
1.3%
4.4107
 
1.0%
3.997
 
0.9%
4.593
 
0.8%
3.883
 
0.7%
3.768
 
0.6%
4.664
 
0.6%
Other values (166)791
 
7.1%
(Missing)9142
82.3%
ValueCountFrequency (%)
1.71
< 0.1%
2.051
< 0.1%
2.21
< 0.1%
2.361
< 0.1%
2.41
< 0.1%
ValueCountFrequency (%)
61
< 0.1%
5.81
< 0.1%
5.71
< 0.1%
5.61
< 0.1%
5.42
< 0.1%

total_protein
Real number (ℝ)

Missing 

Distinct868
Distinct (%)93.4%
Missing10185
Missing (%)91.6%
Infinite0
Infinite (%)0.0%
Mean55.01949408
Minimum12.09
Maximum261.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:38.398527image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum12.09
5-th percentile24.886
Q137.15
median49.1
Q366.7
95-th percentile100.98
Maximum261.25
Range249.16
Interquartile range (IQR)29.55

Descriptive statistics

Standard deviation26.85413344
Coefficient of variation (CV)0.4880839762
Kurtosis7.657704429
Mean55.01949408
Median Absolute Deviation (MAD)14.07
Skewness2.027336524
Sum51113.11
Variance721.1444828
MonotonicityNot monotonic
2025-11-25T16:51:38.447148image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49.723
 
< 0.1%
32.773
 
< 0.1%
54.923
 
< 0.1%
65.152
 
< 0.1%
59.782
 
< 0.1%
30.582
 
< 0.1%
782
 
< 0.1%
44.922
 
< 0.1%
42.072
 
< 0.1%
35.452
 
< 0.1%
Other values (858)906
 
8.2%
(Missing)10185
91.6%
ValueCountFrequency (%)
12.091
< 0.1%
12.991
< 0.1%
14.381
< 0.1%
16.251
< 0.1%
17.441
< 0.1%
ValueCountFrequency (%)
261.251
< 0.1%
209.41
< 0.1%
194.441
< 0.1%
184.781
< 0.1%
184.581
< 0.1%

sodium
Real number (ℝ)

Missing 

Distinct24
Distinct (%)2.3%
Missing10083
Missing (%)90.7%
Infinite0
Infinite (%)0.0%
Mean136.4131911
Minimum122
Maximum147
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:38.490270image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum122
5-th percentile132
Q1135
median136
Q3138
95-th percentile141
Maximum147
Range25
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.788669969
Coefficient of variation (CV)0.02044281749
Kurtosis1.889118491
Mean136.4131911
Median Absolute Deviation (MAD)2
Skewness-0.3178313122
Sum140642
Variance7.776680195
MonotonicityNot monotonic
2025-11-25T16:51:38.530358image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
136177
 
1.6%
137157
 
1.4%
138133
 
1.2%
135131
 
1.2%
13492
 
0.8%
13991
 
0.8%
13363
 
0.6%
14061
 
0.5%
13229
 
0.3%
14126
 
0.2%
Other values (14)71
 
0.6%
(Missing)10083
90.7%
ValueCountFrequency (%)
1221
< 0.1%
1241
< 0.1%
1251
< 0.1%
1262
< 0.1%
1272
< 0.1%
ValueCountFrequency (%)
1471
 
< 0.1%
1462
 
< 0.1%
1444
 
< 0.1%
14310
0.1%
14216
0.1%

potassium
Real number (ℝ)

Missing 

Distinct39
Distinct (%)3.2%
Missing9904
Missing (%)89.1%
Infinite0
Infinite (%)0.0%
Mean4.379330579
Minimum1.05
Maximum6.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:38.571946image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1.05
5-th percentile3.7
Q14.1
median4.3
Q34.6
95-th percentile5.2
Maximum6.6
Range5.55
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation0.4820937223
Coefficient of variation (CV)0.1100838847
Kurtosis3.530739692
Mean4.379330579
Median Absolute Deviation (MAD)0.3
Skewness0.5347409579
Sum5298.99
Variance0.2324143571
MonotonicityNot monotonic
2025-11-25T16:51:38.614432image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
4.3139
 
1.3%
4.2113
 
1.0%
4.4110
 
1.0%
4.1101
 
0.9%
492
 
0.8%
4.683
 
0.7%
4.582
 
0.7%
3.971
 
0.6%
4.767
 
0.6%
4.866
 
0.6%
Other values (29)286
 
2.6%
(Missing)9904
89.1%
ValueCountFrequency (%)
1.051
< 0.1%
2.61
< 0.1%
2.821
< 0.1%
3.271
< 0.1%
3.32
< 0.1%
ValueCountFrequency (%)
6.62
< 0.1%
6.41
 
< 0.1%
6.31
 
< 0.1%
6.23
< 0.1%
6.11
 
< 0.1%

calcium
Real number (ℝ)

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing11113
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean2.31
Minimum2.31
Maximum2.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:38.649058image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum2.31
5-th percentile2.31
Q12.31
median2.31
Q32.31
95-th percentile2.31
Maximum2.31
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean2.31
Median Absolute Deviation (MAD)0
Skewnessnan
Sum2.31
Variancenan
MonotonicityStrictly increasing
2025-11-25T16:51:38.680531image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
2.311
 
< 0.1%
(Missing)11113
> 99.9%
ValueCountFrequency (%)
2.311
< 0.1%
ValueCountFrequency (%)
2.311
< 0.1%

systolic_bp
Real number (ℝ)

Missing 

Distinct211
Distinct (%)4.1%
Missing5938
Missing (%)53.4%
Infinite0
Infinite (%)0.0%
Mean126.3499807
Minimum81
Maximum258.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:38.720088image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum81
5-th percentile102
Q1115
median125
Q3136
95-th percentile155
Maximum258.5
Range177.5
Interquartile range (IQR)21

Descriptive statistics

Standard deviation16.39859049
Coefficient of variation (CV)0.1297870439
Kurtosis2.647640787
Mean126.3499807
Median Absolute Deviation (MAD)10
Skewness0.8747849258
Sum653987.5
Variance268.91377
MonotonicityNot monotonic
2025-11-25T16:51:38.767381image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
124150
 
1.3%
119131
 
1.2%
130131
 
1.2%
123129
 
1.2%
116127
 
1.1%
127125
 
1.1%
129124
 
1.1%
126119
 
1.1%
122119
 
1.1%
135119
 
1.1%
Other values (201)3902
35.1%
(Missing)5938
53.4%
ValueCountFrequency (%)
812
< 0.1%
851
< 0.1%
86.51
< 0.1%
872
< 0.1%
87.51
< 0.1%
ValueCountFrequency (%)
258.51
< 0.1%
2391
< 0.1%
2151
< 0.1%
2131
< 0.1%
2111
< 0.1%

diastolic_bp
Real number (ℝ)

Missing 

Distinct150
Distinct (%)2.9%
Missing5938
Missing (%)53.4%
Infinite0
Infinite (%)0.0%
Mean80.57921175
Minimum39
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:38.815084image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum39
5-th percentile63
Q173
median80
Q387
95-th percentile101
Maximum150
Range111
Interquartile range (IQR)14

Descriptive statistics

Standard deviation11.81065206
Coefficient of variation (CV)0.1465719483
Kurtosis1.157130435
Mean80.57921175
Median Absolute Deviation (MAD)7
Skewness0.526193833
Sum417078
Variance139.4915021
MonotonicityNot monotonic
2025-11-25T16:51:38.860074image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
75182
 
1.6%
78182
 
1.6%
76179
 
1.6%
84176
 
1.6%
79174
 
1.6%
82173
 
1.6%
77171
 
1.5%
83171
 
1.5%
86166
 
1.5%
80162
 
1.5%
Other values (140)3440
31.0%
(Missing)5938
53.4%
ValueCountFrequency (%)
391
 
< 0.1%
403
< 0.1%
461
 
< 0.1%
48.51
 
< 0.1%
492
< 0.1%
ValueCountFrequency (%)
1501
< 0.1%
141.51
< 0.1%
133.51
< 0.1%
1321
< 0.1%
1311
< 0.1%

heart_rate
Real number (ℝ)

Missing 

Distinct85
Distinct (%)1.9%
Missing6596
Missing (%)59.3%
Infinite0
Infinite (%)0.0%
Mean75.77467906
Minimum43
Maximum160
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:38.906224image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum43
5-th percentile56
Q166
median76
Q384
95-th percentile98
Maximum160
Range117
Interquartile range (IQR)18

Descriptive statistics

Standard deviation12.84024749
Coefficient of variation (CV)0.1694530105
Kurtosis0.7468740245
Mean75.77467906
Median Absolute Deviation (MAD)9
Skewness0.4716737255
Sum342350
Variance164.8719556
MonotonicityNot monotonic
2025-11-25T16:51:38.953549image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80200
 
1.8%
78170
 
1.5%
82159
 
1.4%
84156
 
1.4%
60145
 
1.3%
76143
 
1.3%
72137
 
1.2%
68135
 
1.2%
69134
 
1.2%
74129
 
1.2%
Other values (75)3010
27.1%
(Missing)6596
59.3%
ValueCountFrequency (%)
432
 
< 0.1%
441
 
< 0.1%
454
< 0.1%
461
 
< 0.1%
475
< 0.1%
ValueCountFrequency (%)
1601
< 0.1%
1401
< 0.1%
1351
< 0.1%
1331
< 0.1%
1302
< 0.1%

temperature
Real number (ℝ)

Missing 

Distinct48
Distinct (%)1.1%
Missing6826
Missing (%)61.4%
Infinite0
Infinite (%)0.0%
Mean36.38663713
Minimum34.1
Maximum39.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:39.000015image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum34.1
5-th percentile35.7
Q136.1
median36.4
Q336.7
95-th percentile37.2
Maximum39.9
Range5.8
Interquartile range (IQR)0.6

Descriptive statistics

Standard deviation0.4794601552
Coefficient of variation (CV)0.01317681965
Kurtosis3.616970238
Mean36.38663713
Median Absolute Deviation (MAD)0.3
Skewness0.4699462158
Sum156025.9
Variance0.2298820404
MonotonicityNot monotonic
2025-11-25T16:51:39.048108image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
36585
 
5.3%
36.1434
 
3.9%
36.4379
 
3.4%
36.2356
 
3.2%
36.7343
 
3.1%
36.3335
 
3.0%
36.5326
 
2.9%
36.6249
 
2.2%
36.8222
 
2.0%
36.9160
 
1.4%
Other values (38)899
 
8.1%
(Missing)6826
61.4%
ValueCountFrequency (%)
34.11
 
< 0.1%
34.21
 
< 0.1%
34.43
< 0.1%
34.62
< 0.1%
34.71
 
< 0.1%
ValueCountFrequency (%)
39.92
< 0.1%
39.71
< 0.1%
39.51
< 0.1%
39.11
< 0.1%
38.92
< 0.1%

respiratory_rate
Real number (ℝ)

Missing 

Distinct15
Distinct (%)0.7%
Missing8941
Missing (%)80.4%
Infinite0
Infinite (%)0.0%
Mean17.85365854
Minimum11
Maximum52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:39.088703image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile14
Q117
median18
Q319
95-th percentile21
Maximum52
Range41
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.208457648
Coefficient of variation (CV)0.1236977644
Kurtosis26.20743221
Mean17.85365854
Median Absolute Deviation (MAD)1
Skewness1.314367081
Sum38796
Variance4.877285182
MonotonicityNot monotonic
2025-11-25T16:51:39.122879image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
18806
 
7.3%
20371
 
3.3%
16296
 
2.7%
19184
 
1.7%
17147
 
1.3%
14100
 
0.9%
2162
 
0.6%
1555
 
0.5%
1349
 
0.4%
2244
 
0.4%
Other values (5)59
 
0.5%
(Missing)8941
80.4%
ValueCountFrequency (%)
111
 
< 0.1%
1234
 
0.3%
1349
0.4%
14100
0.9%
1555
0.5%
ValueCountFrequency (%)
521
 
< 0.1%
245
 
< 0.1%
2318
 
0.2%
2244
0.4%
2162
0.6%

oxygen_saturation
Real number (ℝ)

Missing 

Distinct12
Distinct (%)0.6%
Missing8987
Missing (%)80.9%
Infinite0
Infinite (%)0.0%
Mean97.99294781
Minimum89
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:39.158941image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum89
5-th percentile96
Q197
median98
Q399
95-th percentile100
Maximum100
Range11
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.361494084
Coefficient of variation (CV)0.01389379659
Kurtosis2.331273282
Mean97.99294781
Median Absolute Deviation (MAD)1
Skewness-0.9867855475
Sum208431
Variance1.853666142
MonotonicityNot monotonic
2025-11-25T16:51:39.196114image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
99676
 
6.1%
98581
 
5.2%
97358
 
3.2%
96216
 
1.9%
100206
 
1.9%
9572
 
0.6%
948
 
0.1%
934
 
< 0.1%
902
 
< 0.1%
912
 
< 0.1%
Other values (2)2
 
< 0.1%
(Missing)8987
80.9%
ValueCountFrequency (%)
891
 
< 0.1%
902
< 0.1%
912
< 0.1%
921
 
< 0.1%
934
< 0.1%
ValueCountFrequency (%)
100206
 
1.9%
99676
6.1%
98581
5.2%
97358
3.2%
96216
 
1.9%

height_m
Real number (ℝ)

Missing 

Distinct337
Distinct (%)5.2%
Missing4609
Missing (%)41.5%
Infinite0
Infinite (%)0.0%
Mean1.653187548
Minimum1.01
Maximum2.01
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:39.241216image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1.01
5-th percentile1.51
Q11.584
median1.65
Q31.72
95-th percentile1.82
Maximum2.01
Range1
Interquartile range (IQR)0.136

Descriptive statistics

Standard deviation0.09626218808
Coefficient of variation (CV)0.058228232
Kurtosis0.6158418246
Mean1.653187548
Median Absolute Deviation (MAD)0.07
Skewness0.1008645781
Sum10753.985
Variance0.009266408855
MonotonicityNot monotonic
2025-11-25T16:51:39.288617image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.65268
 
2.4%
1.6257
 
2.3%
1.63240
 
2.2%
1.7227
 
2.0%
1.62222
 
2.0%
1.64221
 
2.0%
1.67217
 
2.0%
1.72211
 
1.9%
1.58204
 
1.8%
1.69202
 
1.8%
Other values (327)4236
38.1%
(Missing)4609
41.5%
ValueCountFrequency (%)
1.011
< 0.1%
1.051
< 0.1%
1.151
< 0.1%
1.191
< 0.1%
1.21
< 0.1%
ValueCountFrequency (%)
2.012
< 0.1%
1.991
< 0.1%
1.972
< 0.1%
1.962
< 0.1%
1.952
< 0.1%

weight_kg
Real number (ℝ)

Missing 

Distinct806
Distinct (%)12.1%
Missing4477
Missing (%)40.3%
Infinite0
Infinite (%)0.0%
Mean70.7659545
Minimum34
Maximum200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:39.334049image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum34
5-th percentile49
Q158.8
median67.9
Q380.2
95-th percentile101.8
Maximum200
Range166
Interquartile range (IQR)21.4

Descriptive statistics

Standard deviation16.62313684
Coefficient of variation (CV)0.2349030259
Kurtosis1.739869122
Mean70.7659545
Median Absolute Deviation (MAD)10.4
Skewness0.9815325609
Sum469673.64
Variance276.3286786
MonotonicityNot monotonic
2025-11-25T16:51:39.381386image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6561
 
0.5%
6059
 
0.5%
7058
 
0.5%
5545
 
0.4%
7543
 
0.4%
6140
 
0.4%
5639
 
0.4%
6836
 
0.3%
8036
 
0.3%
7436
 
0.3%
Other values (796)6184
55.6%
(Missing)4477
40.3%
ValueCountFrequency (%)
341
< 0.1%
34.11
< 0.1%
351
< 0.1%
35.11
< 0.1%
35.51
< 0.1%
ValueCountFrequency (%)
2001
< 0.1%
1711
< 0.1%
168.81
< 0.1%
162.21
< 0.1%
153.91
< 0.1%

bmi
Real number (ℝ)

Missing 

Distinct2504
Distinct (%)37.9%
Missing4503
Missing (%)40.5%
Infinite0
Infinite (%)0.0%
Mean26.05759331
Minimum14
Maximum70.02555933
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:39.426053image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile18.16315667
Q121.20717902
median24.8
Q329.7
95-th percentile38.20009183
Maximum70.02555933
Range56.02555933
Interquartile range (IQR)8.492820982

Descriptive statistics

Standard deviation6.434987088
Coefficient of variation (CV)0.2469524722
Kurtosis2.007195992
Mean26.05759331
Median Absolute Deviation (MAD)4
Skewness1.119593814
Sum172266.7494
Variance41.40905883
MonotonicityNot monotonic
2025-11-25T16:51:39.469331image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21.552
 
0.5%
20.844
 
0.4%
21.941
 
0.4%
20.541
 
0.4%
22.941
 
0.4%
19.341
 
0.4%
2340
 
0.4%
21.240
 
0.4%
22.239
 
0.4%
21.439
 
0.4%
Other values (2494)6193
55.7%
(Missing)4503
40.5%
ValueCountFrequency (%)
141
< 0.1%
14.21
< 0.1%
14.61
< 0.1%
14.71
< 0.1%
14.82
< 0.1%
ValueCountFrequency (%)
70.025559331
< 0.1%
67.296786391
< 0.1%
65.891
< 0.1%
62.841
< 0.1%
60.386473431
< 0.1%

waist_circumference
Real number (ℝ)

Missing 

Distinct111
Distinct (%)19.2%
Missing10537
Missing (%)94.8%
Infinite0
Infinite (%)0.0%
Mean88.4305026
Minimum59
Maximum151
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:39.516322image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum59
5-th percentile68
Q178
median87
Q397
95-th percentile115.8
Maximum151
Range92
Interquartile range (IQR)19

Descriptive statistics

Standard deviation14.87395089
Coefficient of variation (CV)0.1681993255
Kurtosis1.290483994
Mean88.4305026
Median Absolute Deviation (MAD)9
Skewness0.9342595324
Sum51024.4
Variance221.2344152
MonotonicityNot monotonic
2025-11-25T16:51:39.561948image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8723
 
0.2%
8120
 
0.2%
8519
 
0.2%
7819
 
0.2%
8918
 
0.2%
8617
 
0.2%
7416
 
0.1%
7916
 
0.1%
7615
 
0.1%
8013
 
0.1%
Other values (101)401
 
3.6%
(Missing)10537
94.8%
ValueCountFrequency (%)
591
 
< 0.1%
612
< 0.1%
621
 
< 0.1%
634
< 0.1%
641
 
< 0.1%
ValueCountFrequency (%)
1511
< 0.1%
1451
< 0.1%
143.52
< 0.1%
1401
< 0.1%
1331
< 0.1%

temp_mean_c
Real number (ℝ)

Missing 

Distinct1727
Distinct (%)15.9%
Missing263
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean16.03774531
Minimum-10.05432129
Maximum26.97485352
Zeros0
Zeros (%)0.0%
Negative3
Negative (%)< 0.1%
Memory size87.0 KiB
2025-11-25T16:51:39.605899image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-10.05432129
5-th percentile9.25579834
Q112.33511353
median15.74066162
Q320.20108032
95-th percentile23.19146729
Maximum26.97485352
Range37.0291748
Interquartile range (IQR)7.865966797

Descriptive statistics

Standard deviation4.588166356
Coefficient of variation (CV)0.286085498
Kurtosis-0.7230262351
Mean16.03774531
Median Absolute Deviation (MAD)3.848388672
Skewness-0.05506199227
Sum174025.5744
Variance21.05127051
MonotonicityNot monotonic
2025-11-25T16:51:39.654443image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23.85656738162
 
1.5%
10.2912292582
 
0.7%
12.1875305275
 
0.7%
10.2523193471
 
0.6%
12.7768249568
 
0.6%
15.7406616263
 
0.6%
10.6177978562
 
0.6%
11.8192138756
 
0.5%
13.0397949254
 
0.5%
13.393402150
 
0.4%
Other values (1717)10108
90.9%
(Missing)263
 
2.4%
ValueCountFrequency (%)
-10.054321293
 
< 0.1%
2.7753906251
 
< 0.1%
4.1207580578
0.1%
4.2512817384
< 0.1%
4.3188476563
 
< 0.1%
ValueCountFrequency (%)
26.974853522
 
< 0.1%
26.680236827
0.1%
26.322509774
< 0.1%
26.032592774
< 0.1%
26.010040287
0.1%

temp_max_c
Real number (ℝ)

Missing 

Distinct1723
Distinct (%)15.9%
Missing263
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean23.2515071
Minimum5.698150635
Maximum36.24139404
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:39.784008image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum5.698150635
5-th percentile15.89398193
Q120.30233765
median23.03268433
Q326.62512207
95-th percentile30.65420532
Maximum36.24139404
Range30.54324341
Interquartile range (IQR)6.322784424

Descriptive statistics

Standard deviation4.393749091
Coefficient of variation (CV)0.1889662065
Kurtosis-0.4525748162
Mean23.2515071
Median Absolute Deviation (MAD)3.149841309
Skewness-0.03171967964
Sum252302.1035
Variance19.30503108
MonotonicityNot monotonic
2025-11-25T16:51:39.833595image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30.65509033162
 
1.5%
16.7379150482
 
0.7%
20.5021362375
 
0.7%
15.7619934171
 
0.6%
21.3963928268
 
0.6%
23.3562011763
 
0.6%
19.0531005962
 
0.6%
22.9240112360
 
0.5%
21.2759704656
 
0.5%
22.5196838454
 
0.5%
Other values (1713)10098
90.9%
(Missing)263
 
2.4%
ValueCountFrequency (%)
5.6981506351
 
< 0.1%
8.7833557133
< 0.1%
9.5418701172
< 0.1%
10.096374514
< 0.1%
10.154022222
< 0.1%
ValueCountFrequency (%)
36.241394044
< 0.1%
34.804138182
 
< 0.1%
34.580596927
0.1%
34.516265874
< 0.1%
33.421691897
0.1%

temp_min_c
Real number (ℝ)

Missing 

Distinct1725
Distinct (%)15.9%
Missing263
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean9.758401615
Minimum-11.76116943
Maximum20.26873779
Zeros0
Zeros (%)0.0%
Negative175
Negative (%)1.6%
Memory size87.0 KiB
2025-11-25T16:51:39.885787image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-11.76116943
5-th percentile1.618133545
Q15.343292236
median9.845123291
Q314.46630859
95-th percentile17.44021606
Maximum20.26873779
Range32.02990723
Interquartile range (IQR)9.123016357

Descriptive statistics

Standard deviation5.259556141
Coefficient of variation (CV)0.5389772166
Kurtosis-1.109494087
Mean9.758401615
Median Absolute Deviation (MAD)4.56362915
Skewness-0.1024855153
Sum105888.4159
Variance27.6629308
MonotonicityNot monotonic
2025-11-25T16:51:39.934411image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16.33206177162
 
1.5%
0.96990966882
 
0.7%
1.90200805775
 
0.7%
6.47686767671
 
0.6%
2.76837158268
 
0.6%
9.31896972763
 
0.6%
2.11886596762
 
0.6%
3.24865722756
 
0.5%
5.67422485454
 
0.5%
6.10641479550
 
0.4%
Other values (1715)10108
90.9%
(Missing)263
 
2.4%
ValueCountFrequency (%)
-11.761169433
 
< 0.1%
-1.9614868168
 
0.1%
-1.90347299
0.1%
-1.87918090822
0.2%
-1.6376342774
 
< 0.1%
ValueCountFrequency (%)
20.268737798
0.1%
19.74600221
 
< 0.1%
19.69964611
0.1%
19.633605961
 
< 0.1%
19.5412902814
0.1%

temp_range_c
Real number (ℝ)

Missing 

Distinct1725
Distinct (%)15.9%
Missing263
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean13.49310548
Minimum2.219543457
Maximum21.99676514
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:39.981710image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum2.219543457
5-th percentile6.919128418
Q111.26548767
median13.87136841
Q315.99832153
95-th percentile18.62802124
Maximum21.99676514
Range19.77722168
Interquartile range (IQR)4.732833862

Descriptive statistics

Standard deviation3.571651144
Coefficient of variation (CV)0.264701936
Kurtosis-0.04825905213
Mean13.49310548
Median Absolute Deviation (MAD)2.326446533
Skewness-0.4808117512
Sum146413.6876
Variance12.7566919
MonotonicityNot monotonic
2025-11-25T16:51:40.030437image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.32302856162
 
1.5%
15.7680053782
 
0.7%
18.6001281775
 
0.7%
9.28512573271
 
0.6%
18.6280212468
 
0.6%
14.0372314563
 
0.6%
16.9342346262
 
0.6%
18.0273132356
 
0.5%
16.8454589854
 
0.5%
16.0966186550
 
0.4%
Other values (1715)10108
90.9%
(Missing)263
 
2.4%
ValueCountFrequency (%)
2.21954345711
0.1%
2.2328796392
 
< 0.1%
2.6097412111
 
< 0.1%
2.6834106456
0.1%
2.8407592771
 
< 0.1%
ValueCountFrequency (%)
21.9967651425
0.2%
21.4695434616
0.1%
21.440765382
 
< 0.1%
20.971221925
 
< 0.1%
20.6654968331
0.3%

temp_lag1d
Real number (ℝ)

Missing 

Distinct1727
Distinct (%)15.9%
Missing263
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean16.03774531
Minimum-10.05432129
Maximum26.97485352
Zeros0
Zeros (%)0.0%
Negative3
Negative (%)< 0.1%
Memory size87.0 KiB
2025-11-25T16:51:40.079835image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-10.05432129
5-th percentile9.25579834
Q112.33511353
median15.74066162
Q320.20108032
95-th percentile23.19146729
Maximum26.97485352
Range37.0291748
Interquartile range (IQR)7.865966797

Descriptive statistics

Standard deviation4.588166356
Coefficient of variation (CV)0.286085498
Kurtosis-0.7230262351
Mean16.03774531
Median Absolute Deviation (MAD)3.848388672
Skewness-0.05506199227
Sum174025.5744
Variance21.05127051
MonotonicityNot monotonic
2025-11-25T16:51:40.128840image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23.85656738162
 
1.5%
10.2912292582
 
0.7%
12.1875305275
 
0.7%
10.2523193471
 
0.6%
12.7768249568
 
0.6%
15.7406616263
 
0.6%
10.6177978562
 
0.6%
11.8192138756
 
0.5%
13.0397949254
 
0.5%
13.393402150
 
0.4%
Other values (1717)10108
90.9%
(Missing)263
 
2.4%
ValueCountFrequency (%)
-10.054321293
 
< 0.1%
2.7753906251
 
< 0.1%
4.1207580578
0.1%
4.2512817384
< 0.1%
4.3188476563
 
< 0.1%
ValueCountFrequency (%)
26.974853522
 
< 0.1%
26.680236827
0.1%
26.322509774
< 0.1%
26.032592774
< 0.1%
26.010040287
0.1%

temp_lag3d
Real number (ℝ)

Missing 

Distinct1730
Distinct (%)15.9%
Missing263
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean15.98878696
Minimum3.178507487
Maximum26.68509928
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:40.175661image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum3.178507487
5-th percentile9.508117676
Q112.34500122
median15.68138631
Q320.02757772
95-th percentile22.35461426
Maximum26.68509928
Range23.5065918
Interquartile range (IQR)7.682576497

Descriptive statistics

Standard deviation4.409026881
Coefficient of variation (CV)0.275757435
Kurtosis-1.058369912
Mean15.98878696
Median Absolute Deviation (MAD)3.838531494
Skewness-0.02844949314
Sum173494.3273
Variance19.43951803
MonotonicityNot monotonic
2025-11-25T16:51:40.223961image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22.29105632162
 
1.5%
11.7441406282
 
0.7%
13.3635864375
 
0.7%
11.9533284571
 
0.6%
12.7124226968
 
0.6%
13.6089986263
 
0.6%
10.7179463762
 
0.6%
10.7154337656
 
0.5%
13.3955891954
 
0.5%
13.3854166750
 
0.4%
Other values (1720)10108
90.9%
(Missing)263
 
2.4%
ValueCountFrequency (%)
3.1785074873
 
< 0.1%
4.3595479333
 
< 0.1%
4.65198771222
0.2%
5.4486897798
 
0.1%
5.5199483241
 
< 0.1%
ValueCountFrequency (%)
26.685099287
0.1%
26.598510742
 
< 0.1%
25.666870122
 
< 0.1%
25.658264161
 
< 0.1%
25.634379071
 
< 0.1%

temp_lag7d
Real number (ℝ)

Missing 

Distinct1730
Distinct (%)15.9%
Missing263
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean15.94063694
Minimum3.370261056
Maximum24.8702567
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:40.271503image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum3.370261056
5-th percentile9.840488979
Q112.36106655
median15.74924142
Q319.82111032
95-th percentile22.15353394
Maximum24.8702567
Range21.49999564
Interquartile range (IQR)7.460043771

Descriptive statistics

Standard deviation4.245276938
Coefficient of variation (CV)0.266317899
Kurtosis-1.177041786
Mean15.94063694
Median Absolute Deviation (MAD)3.669747489
Skewness-0.01872978704
Sum172971.8514
Variance18.02237628
MonotonicityNot monotonic
2025-11-25T16:51:40.318182image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20.44643729162
 
1.5%
13.1411525282
 
0.7%
13.4962376275
 
0.7%
12.7222900471
 
0.6%
12.0794939368
 
0.6%
12.494672563
 
0.6%
11.3726545162
 
0.6%
10.271632656
 
0.5%
12.674944254
 
0.5%
12.1921561150
 
0.4%
Other values (1720)10108
90.9%
(Missing)263
 
2.4%
ValueCountFrequency (%)
3.3702610563
 
< 0.1%
3.7983311244
< 0.1%
4.1751926978
0.1%
4.7369777133
 
< 0.1%
6.0393633162
 
< 0.1%
ValueCountFrequency (%)
24.87025672
< 0.1%
24.818655831
 
< 0.1%
24.807586672
< 0.1%
24.44933211
 
< 0.1%
24.436963763
< 0.1%

temp_lag14d
Real number (ℝ)

Missing 

Distinct1730
Distinct (%)15.9%
Missing263
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean15.93380508
Minimum7.199545724
Maximum24.44469343
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:40.363165image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum7.199545724
5-th percentile9.966676985
Q112.24809919
median15.62426758
Q319.8155147
95-th percentile21.94070653
Maximum24.44469343
Range17.24514771
Interquartile range (IQR)7.56741551

Descriptive statistics

Standard deviation4.181770319
Coefficient of variation (CV)0.2624464337
Kurtosis-1.366119193
Mean15.93380508
Median Absolute Deviation (MAD)3.78818621
Skewness0.01394708341
Sum172897.7189
Variance17.487203
MonotonicityNot monotonic
2025-11-25T16:51:40.411907image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21.32225473162
 
1.5%
12.6103232282
 
0.7%
12.8066493475
 
0.7%
11.7492239871
 
0.6%
12.3772190668
 
0.6%
12.739637163
 
0.6%
9.96667698562
 
0.6%
10.8221435556
 
0.5%
11.3818468454
 
0.5%
11.2324327750
 
0.4%
Other values (1720)10108
90.9%
(Missing)263
 
2.4%
ValueCountFrequency (%)
7.1995457242
 
< 0.1%
7.4956403463
< 0.1%
7.6580309195
< 0.1%
7.738660544
< 0.1%
7.8528551373
< 0.1%
ValueCountFrequency (%)
24.444693431
 
< 0.1%
23.584363663
 
< 0.1%
23.577667242
 
< 0.1%
23.3101719410
0.1%
23.296425963
 
< 0.1%

temp_lag21d
Real number (ℝ)

Missing 

Distinct1731
Distinct (%)16.0%
Missing263
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean15.90691129
Minimum8.262842088
Maximum23.75516183
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:40.460366image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum8.262842088
5-th percentile10.0581665
Q112.12665376
median15.88231405
Q319.69606236
95-th percentile21.95376151
Maximum23.75516183
Range15.49231974
Interquartile range (IQR)7.569408598

Descriptive statistics

Standard deviation4.148531399
Coefficient of variation (CV)0.2608005617
Kurtosis-1.444590068
Mean15.90691129
Median Absolute Deviation (MAD)3.787498837
Skewness0.02141054456
Sum172605.8944
Variance17.21031277
MonotonicityNot monotonic
2025-11-25T16:51:40.509280image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21.31667655162
 
1.5%
12.6318635582
 
0.7%
12.6018182775
 
0.7%
11.5264006171
 
0.6%
11.6143958768
 
0.6%
11.8597586563
 
0.6%
10.7272091862
 
0.6%
10.0683288656
 
0.5%
11.122201154
 
0.5%
10.8296247250
 
0.4%
Other values (1721)10108
90.9%
(Missing)263
 
2.4%
ValueCountFrequency (%)
8.2628420881
 
< 0.1%
8.4567507792
< 0.1%
8.478070941
 
< 0.1%
8.5375148233
< 0.1%
8.5759306411
 
< 0.1%
ValueCountFrequency (%)
23.755161831
 
< 0.1%
23.014867875
< 0.1%
22.939258397
0.1%
22.925371443
< 0.1%
22.925077892
 
< 0.1%

temp_lag30d
Real number (ℝ)

Missing 

Distinct1731
Distinct (%)16.0%
Missing263
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean15.88796249
Minimum8.54367981
Maximum24.15265198
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:40.555844image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum8.54367981
5-th percentile10.12995911
Q111.88150228
median15.92819722
Q319.73080495
95-th percentile21.81818949
Maximum24.15265198
Range15.60897217
Interquartile range (IQR)7.849302673

Descriptive statistics

Standard deviation4.124626181
Coefficient of variation (CV)0.2596069939
Kurtosis-1.499597251
Mean15.88796249
Median Absolute Deviation (MAD)3.983812459
Skewness0.02704590165
Sum172400.281
Variance17.01254113
MonotonicityNot monotonic
2025-11-25T16:51:40.605308image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21.58579305162
 
1.5%
11.9443847782
 
0.7%
12.0236358675
 
0.7%
10.8333343571
 
0.6%
11.1074971568
 
0.6%
11.3586344463
 
0.6%
10.5476389662
 
0.6%
10.6309722956
 
0.5%
10.985960954
 
0.5%
10.9288909950
 
0.4%
Other values (1721)10108
90.9%
(Missing)263
 
2.4%
ValueCountFrequency (%)
8.543679811
 
< 0.1%
8.574196372
< 0.1%
8.574885053
< 0.1%
8.6541595461
 
< 0.1%
8.6962738041
 
< 0.1%
ValueCountFrequency (%)
24.152651981
 
< 0.1%
22.648343916
0.1%
22.622926843
 
< 0.1%
22.612386072
 
< 0.1%
22.585823579
0.1%

temp_variability_7d
Real number (ℝ)

Missing 

Distinct1731
Distinct (%)16.0%
Missing263
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean1.650979217
Minimum0.1016849596
Maximum10.73499044
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:40.655962image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.1016849596
5-th percentile0.5440874841
Q11.005314726
median1.48964872
Q32.113210675
95-th percentile3.357089536
Maximum10.73499044
Range10.63330548
Interquartile range (IQR)1.107895949

Descriptive statistics

Standard deviation0.9392297994
Coefficient of variation (CV)0.5688925638
Kurtosis13.01869866
Mean1.650979217
Median Absolute Deviation (MAD)0.5277872777
Skewness2.160084743
Sum17914.77548
Variance0.8821526161
MonotonicityNot monotonic
2025-11-25T16:51:40.702839image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.331820953162
 
1.5%
1.86259919382
 
0.7%
1.41089383375
 
0.7%
1.14112706471
 
0.6%
1.16789879568
 
0.6%
1.81712047863
 
0.6%
0.733379452762
 
0.6%
0.851341891356
 
0.5%
1.06649895354
 
0.5%
1.53557937250
 
0.4%
Other values (1721)10108
90.9%
(Missing)263
 
2.4%
ValueCountFrequency (%)
0.10168495965
 
< 0.1%
0.163827568412
0.1%
0.17930814052
 
< 0.1%
0.184424176615
0.1%
0.2334071699
0.1%
ValueCountFrequency (%)
10.734990443
 
< 0.1%
10.48028248
0.1%
10.236487064
< 0.1%
9.8890278593
 
< 0.1%
8.1350970393
 
< 0.1%

temp_variability_30d
Real number (ℝ)

Missing 

Distinct1731
Distinct (%)16.0%
Missing263
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean2.149724415
Minimum0.76272747
Maximum5.809222506
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:40.749980image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.76272747
5-th percentile1.198858245
Q11.674917399
median2.04513793
Q32.532525062
95-th percentile3.327320984
Maximum5.809222506
Range5.046495036
Interquartile range (IQR)0.8576076627

Descriptive statistics

Standard deviation0.6727669696
Coefficient of variation (CV)0.3129549839
Kurtosis1.947413253
Mean2.149724415
Median Absolute Deviation (MAD)0.4178164191
Skewness0.9363140526
Sum23326.65963
Variance0.4526153953
MonotonicityNot monotonic
2025-11-25T16:51:40.797344image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.071289663162
 
1.5%
1.62732151182
 
0.7%
1.60172817375
 
0.7%
2.01489846171
 
0.6%
1.86921271668
 
0.6%
1.96945037763
 
0.6%
1.90728565562
 
0.6%
1.91710456456
 
0.5%
2.15992351654
 
0.5%
2.12613992850
 
0.4%
Other values (1721)10108
90.9%
(Missing)263
 
2.4%
ValueCountFrequency (%)
0.762727479
0.1%
0.777815067816
0.1%
0.783638241920
0.2%
0.786607437914
0.1%
0.81573361969
0.1%
ValueCountFrequency (%)
5.8092225062
 
< 0.1%
5.8061310213
 
< 0.1%
5.8049255474
< 0.1%
5.8001849718
0.1%
5.7905557283
 
< 0.1%

apparent_temp
Real number (ℝ)

Missing 

Distinct1723
Distinct (%)15.9%
Missing263
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean29.02601632
Minimum3.507736217
Maximum53.4665569
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:40.841726image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum3.507736217
5-th percentile17.01068357
Q123.8339528
median28.35820779
Q334.65849753
95-th percentile42.19438875
Maximum53.4665569
Range49.95882069
Interquartile range (IQR)10.82454473

Descriptive statistics

Standard deviation7.493159728
Coefficient of variation (CV)0.2581532252
Kurtosis-0.4980056038
Mean29.02601632
Median Absolute Deviation (MAD)5.444858296
Skewness0.1487535903
Sum314961.3031
Variance56.14744271
MonotonicityNot monotonic
2025-11-25T16:51:40.888145image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42.19609861162
 
1.5%
18.2709018982
 
0.7%
24.1572885475
 
0.7%
16.8155601271
 
0.6%
25.6194405468
 
0.6%
28.909399663
 
0.6%
21.839997862
 
0.6%
28.1737746160
 
0.5%
25.421118556
 
0.5%
27.4907489954
 
0.5%
Other values (1713)10098
90.9%
(Missing)263
 
2.4%
ValueCountFrequency (%)
3.5077362171
 
< 0.1%
7.2580098443
< 0.1%
8.2246423622
< 0.1%
8.9424289724
< 0.1%
9.0175918412
< 0.1%
ValueCountFrequency (%)
53.46655694
< 0.1%
50.475632292
 
< 0.1%
50.01612397
0.1%
49.88416924
< 0.1%
47.658406937
0.1%

temp_anomaly
Real number (ℝ)

Missing 

Distinct1731
Distinct (%)16.0%
Missing263
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean0.1497828259
Minimum-20.89914347
Maximum7.873060099
Zeros0
Zeros (%)0.0%
Negative5439
Negative (%)48.9%
Memory size87.0 KiB
2025-11-25T16:51:40.932466image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-20.89914347
5-th percentile-3.913265991
Q1-1.3931132
median-0.01201477051
Q31.787661743
95-th percentile4.585971069
Maximum7.873060099
Range28.77220357
Interquartile range (IQR)3.180774943

Descriptive statistics

Standard deviation2.543077384
Coefficient of variation (CV)16.97843107
Kurtosis1.426339639
Mean0.1497828259
Median Absolute Deviation (MAD)1.603962199
Skewness-0.02207669288
Sum1625.293444
Variance6.467242582
MonotonicityNot monotonic
2025-11-25T16:51:40.977348image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.270774333162
 
1.5%
-1.65315551882
 
0.7%
0.163894653375
 
0.7%
-0.581015014671
 
0.6%
1.66932779968
 
0.6%
4.38202718163
 
0.6%
0.0701588948662
 
0.6%
1.18824157756
 
0.5%
2.05383402554
 
0.5%
2.46451110850
 
0.4%
Other values (1721)10108
90.9%
(Missing)263
 
2.4%
ValueCountFrequency (%)
-20.899143473
< 0.1%
-10.616883345
< 0.1%
-9.2891357424
< 0.1%
-8.9442260741
 
< 0.1%
-8.2044820151
 
< 0.1%
ValueCountFrequency (%)
7.8730600991
 
< 0.1%
7.4131764734
< 0.1%
7.3442464198
0.1%
7.2592651374
< 0.1%
6.9910390224
< 0.1%

heat_wave_day
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.06541299262
Minimum0
Maximum1
Zeros10387
Zeros (%)93.5%
Negative0
Negative (%)0.0%
Memory size87.0 KiB
2025-11-25T16:51:41.015001image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2472643002
Coefficient of variation (CV)3.780048738
Kurtosis10.36267536
Mean0.06541299262
Median Absolute Deviation (MAD)0
Skewness3.515794447
Sum727
Variance0.06113963415
MonotonicityNot monotonic
2025-11-25T16:51:41.048447image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
010387
93.5%
1727
 
6.5%
ValueCountFrequency (%)
010387
93.5%
1727
 
6.5%
ValueCountFrequency (%)
1727
 
6.5%
010387
93.5%

heat_stress_category
Text

Missing 

Distinct5
Distinct (%)< 0.1%
Missing263
Missing (%)2.4%
Memory size87.0 KiB
2025-11-25T16:51:41.082848image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length8.33204313
Min length3

Characters and Unicode

Total characters90411
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowComfortable
2nd rowComfortable
3rd rowComfortable
4th rowComfortable
5th rowComfortable
ValueCountFrequency (%)
comfortable6814
62.8%
warm3033
27.9%
hot723
 
6.7%
cold277
 
2.6%
extreme4
 
< 0.1%
heat4
 
< 0.1%
2025-11-25T16:51:41.159804image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o14628
16.2%
m9851
10.9%
r9851
10.9%
a9851
10.9%
t7545
8.3%
C7091
7.8%
l7091
7.8%
e6826
7.5%
f6814
7.5%
b6814
7.5%
Other values (6)4049
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter79552
88.0%
Uppercase Letter10855
 
12.0%
Space Separator4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o14628
18.4%
m9851
12.4%
r9851
12.4%
a9851
12.4%
t7545
9.5%
l7091
8.9%
e6826
8.6%
f6814
8.6%
b6814
8.6%
d277
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
C7091
65.3%
W3033
27.9%
H727
 
6.7%
E4
 
< 0.1%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin90407
> 99.9%
Common4
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o14628
16.2%
m9851
10.9%
r9851
10.9%
a9851
10.9%
t7545
8.3%
C7091
7.8%
l7091
7.8%
e6826
7.6%
f6814
7.5%
b6814
7.5%
Other values (5)4045
 
4.5%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII90411
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o14628
16.2%
m9851
10.9%
r9851
10.9%
a9851
10.9%
t7545
8.3%
C7091
7.8%
l7091
7.8%
e6826
7.5%
f6814
7.5%
b6814
7.5%
Other values (6)4049
 
4.5%